Seminars
Our virtual seminar series is where we exchange ideas with guest speakers, keeping you up to date with the latest developments and inspiring research topics. Occasionally, Secondmind researchers present their own work as well.
HIGHLIGHT
HIGHLIGHT
HIGHLIGHT
HIGHLIGHT
Seminar
Seminar
Seminar
Seminar
March 28th, 2024
Optimal Experiment Design in Markov Chains
Optimal Experiment Design in Markov Chains
Optimal Experiment Design in Markov Chains
Mojmír Mutný
Mojmír Mutný
Mojmír Mutný
Postdoctoral researcher at ETH Zurich
Postdoctoral researcher at ETH Zurich
Postdoctoral researcher at ETH Zurich
Past seminars
Mickael Binois - Leveraging replication in active learning
We were recently joined by Mickael Binois, to talk about 'Leveraging replication in active learning'.
Jun 24, 2024
Mickael Binois - Leveraging replication in active learning
We were recently joined by Mickael Binois, to talk about 'Leveraging replication in active learning'.
Jun 24, 2024
Mickael Binois - Leveraging replication in active learning
We were recently joined by Mickael Binois, to talk about 'Leveraging replication in active learning'.
Jun 24, 2024
Mickael Binois - Leveraging replication in active learning
We were recently joined by Mickael Binois, to talk about 'Leveraging replication in active learning'.
Jun 24, 2024
Ilija Bogunovic - From Data to Confident Decisions
We were recently joined by Ilija Bogunovic, to talk about 'Robust and Efficient Algorithmic Decision Making'.
Jun 13, 2024
Ilija Bogunovic - From Data to Confident Decisions
We were recently joined by Ilija Bogunovic, to talk about 'Robust and Efficient Algorithmic Decision Making'.
Jun 13, 2024
Ilija Bogunovic - From Data to Confident Decisions
We were recently joined by Ilija Bogunovic, to talk about 'Robust and Efficient Algorithmic Decision Making'.
Jun 13, 2024
Ilija Bogunovic - From Data to Confident Decisions
We were recently joined by Ilija Bogunovic, to talk about 'Robust and Efficient Algorithmic Decision Making'.
Jun 13, 2024
Dario Azzimonti - Preference learning with Gaussian processes
We were recently joined by Dario Azzimonti, to talk about 'Preference learning with Gaussian processes'.
May 23, 2024
Dario Azzimonti - Preference learning with Gaussian processes
We were recently joined by Dario Azzimonti, to talk about 'Preference learning with Gaussian processes'.
May 23, 2024
Dario Azzimonti - Preference learning with Gaussian processes
We were recently joined by Dario Azzimonti, to talk about 'Preference learning with Gaussian processes'.
May 23, 2024
Dario Azzimonti - Preference learning with Gaussian processes
We were recently joined by Dario Azzimonti, to talk about 'Preference learning with Gaussian processes'.
May 23, 2024
Mojmír Mutný - Optimal Experiment Design in Markov Chains
We were recently joined by Mojmír Mutný (ETH Zurich), to talk about 'Optimal Experiment Design in Markov Chains'.
Mar 28, 2024
Mojmír Mutný - Optimal Experiment Design in Markov Chains
We were recently joined by Mojmír Mutný (ETH Zurich), to talk about 'Optimal Experiment Design in Markov Chains'.
Mar 28, 2024
Mojmír Mutný - Optimal Experiment Design in Markov Chains
We were recently joined by Mojmír Mutný (ETH Zurich), to talk about 'Optimal Experiment Design in Markov Chains'.
Mar 28, 2024
Mojmír Mutný - Optimal Experiment Design in Markov Chains
We were recently joined by Mojmír Mutný (ETH Zurich), to talk about 'Optimal Experiment Design in Markov Chains'.
Mar 28, 2024
Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management
We were recently joined by Domenic Di Francesco (The Alan Turing Institute), to talk about 'Data-Centric Engineering for Coherent Risk Management'.
Oct 26, 2023
Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management
We were recently joined by Domenic Di Francesco (The Alan Turing Institute), to talk about 'Data-Centric Engineering for Coherent Risk Management'.
Oct 26, 2023
Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management
We were recently joined by Domenic Di Francesco (The Alan Turing Institute), to talk about 'Data-Centric Engineering for Coherent Risk Management'.
Oct 26, 2023
Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management
We were recently joined by Domenic Di Francesco (The Alan Turing Institute), to talk about 'Data-Centric Engineering for Coherent Risk Management'.
Oct 26, 2023
Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering
We were recently joined by Antonio Del Rio Chanona (Imperial College London), to talk about 'Multi-Fidelity Bayesian Optimization in Chemical Engineering'.
Jul 6, 2023
Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering
We were recently joined by Antonio Del Rio Chanona (Imperial College London), to talk about 'Multi-Fidelity Bayesian Optimization in Chemical Engineering'.
Jul 6, 2023
Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering
We were recently joined by Antonio Del Rio Chanona (Imperial College London), to talk about 'Multi-Fidelity Bayesian Optimization in Chemical Engineering'.
Jul 6, 2023
Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering
We were recently joined by Antonio Del Rio Chanona (Imperial College London), to talk about 'Multi-Fidelity Bayesian Optimization in Chemical Engineering'.
Jul 6, 2023
Luigi Nardi - Harnessing new information in Bayesian optimization
We were recently joined by Luigi Nardi (Lund University, Stanford University and DBtune), to talk about 'Harnessing new information in Bayesian optimization'.
Jun 7, 2023
Luigi Nardi - Harnessing new information in Bayesian optimization
We were recently joined by Luigi Nardi (Lund University, Stanford University and DBtune), to talk about 'Harnessing new information in Bayesian optimization'.
Jun 7, 2023
Luigi Nardi - Harnessing new information in Bayesian optimization
We were recently joined by Luigi Nardi (Lund University, Stanford University and DBtune), to talk about 'Harnessing new information in Bayesian optimization'.
Jun 7, 2023
Luigi Nardi - Harnessing new information in Bayesian optimization
We were recently joined by Luigi Nardi (Lund University, Stanford University and DBtune), to talk about 'Harnessing new information in Bayesian optimization'.
Jun 7, 2023
Christopher Nemeth - Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
We were recently joined by Christopher Nemeth (University of Lancaster), to talk about 'Gradient-Based Bayesian Inference without Learning Rates'.
Feb 23, 2023
Christopher Nemeth - Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
We were recently joined by Christopher Nemeth (University of Lancaster), to talk about 'Gradient-Based Bayesian Inference without Learning Rates'.
Feb 23, 2023
Christopher Nemeth - Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
We were recently joined by Christopher Nemeth (University of Lancaster), to talk about 'Gradient-Based Bayesian Inference without Learning Rates'.
Feb 23, 2023
Christopher Nemeth - Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
We were recently joined by Christopher Nemeth (University of Lancaster), to talk about 'Gradient-Based Bayesian Inference without Learning Rates'.
Feb 23, 2023
David K. Duvenaud - A farewell to GPs
We were recently joined by David Duvenaud (University of Toronto), to talk about 'A farewell to GPs'.
Dec 14, 2022
David K. Duvenaud - A farewell to GPs
We were recently joined by David Duvenaud (University of Toronto), to talk about 'A farewell to GPs'.
Dec 14, 2022
David K. Duvenaud - A farewell to GPs
We were recently joined by David Duvenaud (University of Toronto), to talk about 'A farewell to GPs'.
Dec 14, 2022
David K. Duvenaud - A farewell to GPs
We were recently joined by David Duvenaud (University of Toronto), to talk about 'A farewell to GPs'.
Dec 14, 2022
Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling: the geoML project
We were recently joined by Ítalo Gomes Gonçalves (Universidade Federal do Pampa), to talk about 'Variational Gaussian processes for spatial modeling: the geoML project'.
Nov 23, 2022
Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling: the geoML project
We were recently joined by Ítalo Gomes Gonçalves (Universidade Federal do Pampa), to talk about 'Variational Gaussian processes for spatial modeling: the geoML project'.
Nov 23, 2022
Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling: the geoML project
We were recently joined by Ítalo Gomes Gonçalves (Universidade Federal do Pampa), to talk about 'Variational Gaussian processes for spatial modeling: the geoML project'.
Nov 23, 2022
Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling: the geoML project
We were recently joined by Ítalo Gomes Gonçalves (Universidade Federal do Pampa), to talk about 'Variational Gaussian processes for spatial modeling: the geoML project'.
Nov 23, 2022
Martin Jørgensen - Bézier Gaussian Processes
We were recently joined by Martin Jørgensen (University of Oxford), to talk about 'Bézier Gaussian Processes'.
Nov 10, 2022
Martin Jørgensen - Bézier Gaussian Processes
We were recently joined by Martin Jørgensen (University of Oxford), to talk about 'Bézier Gaussian Processes'.
Nov 10, 2022
Martin Jørgensen - Bézier Gaussian Processes
We were recently joined by Martin Jørgensen (University of Oxford), to talk about 'Bézier Gaussian Processes'.
Nov 10, 2022
Martin Jørgensen - Bézier Gaussian Processes
We were recently joined by Martin Jørgensen (University of Oxford), to talk about 'Bézier Gaussian Processes'.
Nov 10, 2022
Barbara Rakitsch - Interacting ODEs with Gaussian Processes
We were recently joined by Barbara Rakitsch (Bosch Center for Artificial Intelligence), to talk about 'Interacting ODEs with Gaussian Processes'.
Oct 6, 2022
Barbara Rakitsch - Interacting ODEs with Gaussian Processes
We were recently joined by Barbara Rakitsch (Bosch Center for Artificial Intelligence), to talk about 'Interacting ODEs with Gaussian Processes'.
Oct 6, 2022
Barbara Rakitsch - Interacting ODEs with Gaussian Processes
We were recently joined by Barbara Rakitsch (Bosch Center for Artificial Intelligence), to talk about 'Interacting ODEs with Gaussian Processes'.
Oct 6, 2022
Barbara Rakitsch - Interacting ODEs with Gaussian Processes
We were recently joined by Barbara Rakitsch (Bosch Center for Artificial Intelligence), to talk about 'Interacting ODEs with Gaussian Processes'.
Oct 6, 2022
Sebastian Farquhar - Unbiased Active Learning and Testing
We were recently joined by Sebastian Farquhar (University of Oxofrd), to talk about 'Unbiased Active Learning and Testing'.
Sep 16, 2022
Sebastian Farquhar - Unbiased Active Learning and Testing
We were recently joined by Sebastian Farquhar (University of Oxofrd), to talk about 'Unbiased Active Learning and Testing'.
Sep 16, 2022
Sebastian Farquhar - Unbiased Active Learning and Testing
We were recently joined by Sebastian Farquhar (University of Oxofrd), to talk about 'Unbiased Active Learning and Testing'.
Sep 16, 2022
Sebastian Farquhar - Unbiased Active Learning and Testing
We were recently joined by Sebastian Farquhar (University of Oxofrd), to talk about 'Unbiased Active Learning and Testing'.
Sep 16, 2022
Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes
We were recently joined by Pablo Moreno-Muñoz (Technical University of Denmark), to talk about 'Model Recycling with Gaussian Processes'.
Jun 23, 2022
Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes
We were recently joined by Pablo Moreno-Muñoz (Technical University of Denmark), to talk about 'Model Recycling with Gaussian Processes'.
Jun 23, 2022
Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes
We were recently joined by Pablo Moreno-Muñoz (Technical University of Denmark), to talk about 'Model Recycling with Gaussian Processes'.
Jun 23, 2022
Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes
We were recently joined by Pablo Moreno-Muñoz (Technical University of Denmark), to talk about 'Model Recycling with Gaussian Processes'.
Jun 23, 2022
Aryan Deshwal - Bayesian Optimization over Combinatorial Structures
We were recently joined by Aryan Deshwal (Washington State University), to talk about 'Bayesian Optimization over Combinatorial Structures'.
May 26, 2022
Aryan Deshwal - Bayesian Optimization over Combinatorial Structures
We were recently joined by Aryan Deshwal (Washington State University), to talk about 'Bayesian Optimization over Combinatorial Structures'.
May 26, 2022
Aryan Deshwal - Bayesian Optimization over Combinatorial Structures
We were recently joined by Aryan Deshwal (Washington State University), to talk about 'Bayesian Optimization over Combinatorial Structures'.
May 26, 2022
Aryan Deshwal - Bayesian Optimization over Combinatorial Structures
We were recently joined by Aryan Deshwal (Washington State University), to talk about 'Bayesian Optimization over Combinatorial Structures'.
May 26, 2022
François-Xavier Briol - Bayesian Estimation of Integrals: A Multi-task Approach
We had the pleasure to host Francois-Xavier Briol for a virtual seminar. His work on Bayesian quadrature is very relevant to research and applications at Secondmind.ai
Jan 6, 2022
François-Xavier Briol - Bayesian Estimation of Integrals: A Multi-task Approach
We had the pleasure to host Francois-Xavier Briol for a virtual seminar. His work on Bayesian quadrature is very relevant to research and applications at Secondmind.ai
Jan 6, 2022
François-Xavier Briol - Bayesian Estimation of Integrals: A Multi-task Approach
We had the pleasure to host Francois-Xavier Briol for a virtual seminar. His work on Bayesian quadrature is very relevant to research and applications at Secondmind.ai
Jan 6, 2022
François-Xavier Briol - Bayesian Estimation of Integrals: A Multi-task Approach
We had the pleasure to host Francois-Xavier Briol for a virtual seminar. His work on Bayesian quadrature is very relevant to research and applications at Secondmind.ai
Jan 6, 2022
Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes
We were recently joined by Dino Sejdinovic (University of Oxford), to talk about 'Recent Developments at the Interface Between Kernel Embeddings and Gaussian Processes'.
Dec 2, 2021
Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes
We were recently joined by Dino Sejdinovic (University of Oxford), to talk about 'Recent Developments at the Interface Between Kernel Embeddings and Gaussian Processes'.
Dec 2, 2021
Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes
We were recently joined by Dino Sejdinovic (University of Oxford), to talk about 'Recent Developments at the Interface Between Kernel Embeddings and Gaussian Processes'.
Dec 2, 2021
Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes
We were recently joined by Dino Sejdinovic (University of Oxford), to talk about 'Recent Developments at the Interface Between Kernel Embeddings and Gaussian Processes'.
Dec 2, 2021
Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning
We were recently joined by Noémie Jaquier (Karlsruhe Institute of Technology), to talk about 'Bayesian optimization on Riemannian manifolds for robot learning'.
Nov 25, 2021
Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning
We were recently joined by Noémie Jaquier (Karlsruhe Institute of Technology), to talk about 'Bayesian optimization on Riemannian manifolds for robot learning'.
Nov 25, 2021
Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning
We were recently joined by Noémie Jaquier (Karlsruhe Institute of Technology), to talk about 'Bayesian optimization on Riemannian manifolds for robot learning'.
Nov 25, 2021
Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning
We were recently joined by Noémie Jaquier (Karlsruhe Institute of Technology), to talk about 'Bayesian optimization on Riemannian manifolds for robot learning'.
Nov 25, 2021
François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints
We were recently joined by François Bachoc (Toulouse Mathematics Institute), to talk about 'Sequential construction and dimension reduction of Gaussian processes under inequality constraints'.
Nov 25, 2021
François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints
We were recently joined by François Bachoc (Toulouse Mathematics Institute), to talk about 'Sequential construction and dimension reduction of Gaussian processes under inequality constraints'.
Nov 25, 2021
François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints
We were recently joined by François Bachoc (Toulouse Mathematics Institute), to talk about 'Sequential construction and dimension reduction of Gaussian processes under inequality constraints'.
Nov 25, 2021
François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints
We were recently joined by François Bachoc (Toulouse Mathematics Institute), to talk about 'Sequential construction and dimension reduction of Gaussian processes under inequality constraints'.
Nov 25, 2021
Frank Hutter - Towards Deep Learning 2.0: Going to the Meta-Level
We were recently joined by Frank Hutter (University of Freiburg), to talk about 'Towards Deep Learning 2.0: Going to the Meta-Level'.
Nov 11, 2021
Frank Hutter - Towards Deep Learning 2.0: Going to the Meta-Level
We were recently joined by Frank Hutter (University of Freiburg), to talk about 'Towards Deep Learning 2.0: Going to the Meta-Level'.
Nov 11, 2021
Frank Hutter - Towards Deep Learning 2.0: Going to the Meta-Level
We were recently joined by Frank Hutter (University of Freiburg), to talk about 'Towards Deep Learning 2.0: Going to the Meta-Level'.
Nov 11, 2021
Frank Hutter - Towards Deep Learning 2.0: Going to the Meta-Level
We were recently joined by Frank Hutter (University of Freiburg), to talk about 'Towards Deep Learning 2.0: Going to the Meta-Level'.
Nov 11, 2021
Javier González Hernández - Causal Bayesian Optimisation
We were recently joined by Javier González Hernández (Microsoft Research Cambridge), to talk about 'Causal Bayesian Optimisation: don’t do everything, just do the right thing'.
Feb 21, 2021
Javier González Hernández - Causal Bayesian Optimisation
We were recently joined by Javier González Hernández (Microsoft Research Cambridge), to talk about 'Causal Bayesian Optimisation: don’t do everything, just do the right thing'.
Feb 21, 2021
Javier González Hernández - Causal Bayesian Optimisation
We were recently joined by Javier González Hernández (Microsoft Research Cambridge), to talk about 'Causal Bayesian Optimisation: don’t do everything, just do the right thing'.
Feb 21, 2021
Javier González Hernández - Causal Bayesian Optimisation
We were recently joined by Javier González Hernández (Microsoft Research Cambridge), to talk about 'Causal Bayesian Optimisation: don’t do everything, just do the right thing'.
Feb 21, 2021
Emtiyaz Khan - Bayesian Principles for Learning-Machines
We were recently joined by Emtiyaz Khan (RIKEN), to talk about 'Bayesian Principles for Learning-Machines'.
Sep 17, 2021
Emtiyaz Khan - Bayesian Principles for Learning-Machines
We were recently joined by Emtiyaz Khan (RIKEN), to talk about 'Bayesian Principles for Learning-Machines'.
Sep 17, 2021
Emtiyaz Khan - Bayesian Principles for Learning-Machines
We were recently joined by Emtiyaz Khan (RIKEN), to talk about 'Bayesian Principles for Learning-Machines'.
Sep 17, 2021
Emtiyaz Khan - Bayesian Principles for Learning-Machines
We were recently joined by Emtiyaz Khan (RIKEN), to talk about 'Bayesian Principles for Learning-Machines'.
Sep 17, 2021
Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning
Dr Ciara Pike-Burke (Imperial College London), gave a talk on 'A unifying view of optimism in episodic reinforcement learning'.
Sep 2, 2021
Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning
Dr Ciara Pike-Burke (Imperial College London), gave a talk on 'A unifying view of optimism in episodic reinforcement learning'.
Sep 2, 2021
Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning
Dr Ciara Pike-Burke (Imperial College London), gave a talk on 'A unifying view of optimism in episodic reinforcement learning'.
Sep 2, 2021
Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning
Dr Ciara Pike-Burke (Imperial College London), gave a talk on 'A unifying view of optimism in episodic reinforcement learning'.
Sep 2, 2021
José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning
We were recently joined by José Miguel Hernández Lobato (University of Cambridge), to talk about 'Probabilistic Methods for Increased Robustness in Machine Learning'.
Jul 15, 2021
José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning
We were recently joined by José Miguel Hernández Lobato (University of Cambridge), to talk about 'Probabilistic Methods for Increased Robustness in Machine Learning'.
Jul 15, 2021
José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning
We were recently joined by José Miguel Hernández Lobato (University of Cambridge), to talk about 'Probabilistic Methods for Increased Robustness in Machine Learning'.
Jul 15, 2021
José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning
We were recently joined by José Miguel Hernández Lobato (University of Cambridge), to talk about 'Probabilistic Methods for Increased Robustness in Machine Learning'.
Jul 15, 2021
Carl Henrik Ek - Modulating surrogates for bayesian optimization
We were recently joined by Carl Henrik Ek to talk about 'Modulating surrogates for bayesian optimization'.
Jun 10, 2021
Carl Henrik Ek - Modulating surrogates for bayesian optimization
We were recently joined by Carl Henrik Ek to talk about 'Modulating surrogates for bayesian optimization'.
Jun 10, 2021
Carl Henrik Ek - Modulating surrogates for bayesian optimization
We were recently joined by Carl Henrik Ek to talk about 'Modulating surrogates for bayesian optimization'.
Jun 10, 2021
Carl Henrik Ek - Modulating surrogates for bayesian optimization
We were recently joined by Carl Henrik Ek to talk about 'Modulating surrogates for bayesian optimization'.
Jun 10, 2021
Peter Stone - Efficient Robot Skill Learning
We were recently joined by Peter Stone (University of Texas at Austin & Sony AI), to talk about 'Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation'.
May 13, 2020
Peter Stone - Efficient Robot Skill Learning
We were recently joined by Peter Stone (University of Texas at Austin & Sony AI), to talk about 'Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation'.
May 13, 2020
Peter Stone - Efficient Robot Skill Learning
We were recently joined by Peter Stone (University of Texas at Austin & Sony AI), to talk about 'Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation'.
May 13, 2020
Peter Stone - Efficient Robot Skill Learning
We were recently joined by Peter Stone (University of Texas at Austin & Sony AI), to talk about 'Efficient Robot Skill Learning: Grounded Simulation Learning and Imitation Learning from Observation'.
May 13, 2020
Laurence Aitchison - Deep Kernel Processes
We were recently joined by Laurence Aitchison (University of Bristol), to talk about 'Deep Kernel Processes?'.
Mar 4, 2021
Laurence Aitchison - Deep Kernel Processes
We were recently joined by Laurence Aitchison (University of Bristol), to talk about 'Deep Kernel Processes?'.
Mar 4, 2021
Laurence Aitchison - Deep Kernel Processes
We were recently joined by Laurence Aitchison (University of Bristol), to talk about 'Deep Kernel Processes?'.
Mar 4, 2021
Laurence Aitchison - Deep Kernel Processes
We were recently joined by Laurence Aitchison (University of Bristol), to talk about 'Deep Kernel Processes?'.
Mar 4, 2021
Andrew G. Wilson - How do we build models that learn and generalize?
We were recently joined by Andrew G. Wilson (New York University), to talk about 'How do we build models that learn and generalize?'.
Jan 21, 2021
Andrew G. Wilson - How do we build models that learn and generalize?
We were recently joined by Andrew G. Wilson (New York University), to talk about 'How do we build models that learn and generalize?'.
Jan 21, 2021
Andrew G. Wilson - How do we build models that learn and generalize?
We were recently joined by Andrew G. Wilson (New York University), to talk about 'How do we build models that learn and generalize?'.
Jan 21, 2021
Andrew G. Wilson - How do we build models that learn and generalize?
We were recently joined by Andrew G. Wilson (New York University), to talk about 'How do we build models that learn and generalize?'.
Jan 21, 2021
Vincent Adam - Sparse methods for markovian GPs
We were recently joined by Vincent Adam (Secondmind & Aalto University), to talk about 'Sparse methods for markovian GPs'.
Jan 14, 2021
Vincent Adam - Sparse methods for markovian GPs
We were recently joined by Vincent Adam (Secondmind & Aalto University), to talk about 'Sparse methods for markovian GPs'.
Jan 14, 2021
Vincent Adam - Sparse methods for markovian GPs
We were recently joined by Vincent Adam (Secondmind & Aalto University), to talk about 'Sparse methods for markovian GPs'.
Jan 14, 2021
Vincent Adam - Sparse methods for markovian GPs
We were recently joined by Vincent Adam (Secondmind & Aalto University), to talk about 'Sparse methods for markovian GPs'.
Jan 14, 2021
M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it
Matthew E. Taylor (University of Alberta) gave a talk on 'Reinforcement Learning in the Real-world: How to “cheat” and still feel good about it'.
Dec 17, 2020
M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it
Matthew E. Taylor (University of Alberta) gave a talk on 'Reinforcement Learning in the Real-world: How to “cheat” and still feel good about it'.
Dec 17, 2020
M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it
Matthew E. Taylor (University of Alberta) gave a talk on 'Reinforcement Learning in the Real-world: How to “cheat” and still feel good about it'.
Dec 17, 2020
M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it
Matthew E. Taylor (University of Alberta) gave a talk on 'Reinforcement Learning in the Real-world: How to “cheat” and still feel good about it'.
Dec 17, 2020
Arthur Guez - Value-driven Hindsight Modelling
We were recently joined by Arthur Guez (Google Deepmind), to talk about 'Value-driven Hindsight Modelling'.
Nov 19, 2020
Arthur Guez - Value-driven Hindsight Modelling
We were recently joined by Arthur Guez (Google Deepmind), to talk about 'Value-driven Hindsight Modelling'.
Nov 19, 2020
Arthur Guez - Value-driven Hindsight Modelling
We were recently joined by Arthur Guez (Google Deepmind), to talk about 'Value-driven Hindsight Modelling'.
Nov 19, 2020
Arthur Guez - Value-driven Hindsight Modelling
We were recently joined by Arthur Guez (Google Deepmind), to talk about 'Value-driven Hindsight Modelling'.
Nov 19, 2020
Alexandra Gessner - Integration for and as Bayesian inference
We were recently joined by Alexandra Gessner (University of Tuebingen), to talk about 'Integration for and as Bayesian inference'.
Nov 12, 2020
Alexandra Gessner - Integration for and as Bayesian inference
We were recently joined by Alexandra Gessner (University of Tuebingen), to talk about 'Integration for and as Bayesian inference'.
Nov 12, 2020
Alexandra Gessner - Integration for and as Bayesian inference
We were recently joined by Alexandra Gessner (University of Tuebingen), to talk about 'Integration for and as Bayesian inference'.
Nov 12, 2020
Alexandra Gessner - Integration for and as Bayesian inference
We were recently joined by Alexandra Gessner (University of Tuebingen), to talk about 'Integration for and as Bayesian inference'.
Nov 12, 2020
Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning
We were recently joined by Dr Arno Solin (Aalto University), to talk about 'Stationary Activations for Uncertainty Calibration in Deep Learning'.
Oct 29, 2020
Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning
We were recently joined by Dr Arno Solin (Aalto University), to talk about 'Stationary Activations for Uncertainty Calibration in Deep Learning'.
Oct 29, 2020
Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning
We were recently joined by Dr Arno Solin (Aalto University), to talk about 'Stationary Activations for Uncertainty Calibration in Deep Learning'.
Oct 29, 2020
Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning
We were recently joined by Dr Arno Solin (Aalto University), to talk about 'Stationary Activations for Uncertainty Calibration in Deep Learning'.
Oct 29, 2020
Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind
Siddharth Reddy (University of California, Berkley), gave a talk on 'Assisting Human Perception and Control using Theory of Mind'.
Oct 22, 2020
Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind
Siddharth Reddy (University of California, Berkley), gave a talk on 'Assisting Human Perception and Control using Theory of Mind'.
Oct 22, 2020
Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind
Siddharth Reddy (University of California, Berkley), gave a talk on 'Assisting Human Perception and Control using Theory of Mind'.
Oct 22, 2020
Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind
Siddharth Reddy (University of California, Berkley), gave a talk on 'Assisting Human Perception and Control using Theory of Mind'.
Oct 22, 2020
Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization
We were recently joined by Peter Frazier (Cornell University & Uber), to talk about 'Knowledge-Gradient Methods for Grey-Box Bayesian Optimization'.
Oct 8, 2022
Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization
We were recently joined by Peter Frazier (Cornell University & Uber), to talk about 'Knowledge-Gradient Methods for Grey-Box Bayesian Optimization'.
Oct 8, 2022
Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization
We were recently joined by Peter Frazier (Cornell University & Uber), to talk about 'Knowledge-Gradient Methods for Grey-Box Bayesian Optimization'.
Oct 8, 2022
Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization
We were recently joined by Peter Frazier (Cornell University & Uber), to talk about 'Knowledge-Gradient Methods for Grey-Box Bayesian Optimization'.
Oct 8, 2022
Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis
Gabriel Dulac-Arnold (Google Research), gave a talk on 'Challenges of Real-world RL: Definition, Implementation, Analysis'.
Oct 1, 2020
Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis
Gabriel Dulac-Arnold (Google Research), gave a talk on 'Challenges of Real-world RL: Definition, Implementation, Analysis'.
Oct 1, 2020
Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis
Gabriel Dulac-Arnold (Google Research), gave a talk on 'Challenges of Real-world RL: Definition, Implementation, Analysis'.
Oct 1, 2020
Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis
Gabriel Dulac-Arnold (Google Research), gave a talk on 'Challenges of Real-world RL: Definition, Implementation, Analysis'.
Oct 1, 2020
Philipp Hennig - Computation under Uncertainty
We were recently joined by Philipp Hennig (University of Tuebingen), to talk about 'Computation under Uncertainty'.
Sep 24, 2020
Philipp Hennig - Computation under Uncertainty
We were recently joined by Philipp Hennig (University of Tuebingen), to talk about 'Computation under Uncertainty'.
Sep 24, 2020
Philipp Hennig - Computation under Uncertainty
We were recently joined by Philipp Hennig (University of Tuebingen), to talk about 'Computation under Uncertainty'.
Sep 24, 2020
Philipp Hennig - Computation under Uncertainty
We were recently joined by Philipp Hennig (University of Tuebingen), to talk about 'Computation under Uncertainty'.
Sep 24, 2020
Magnus Rattray - Non-parametric modelling of gene expression in time and space
We were recently joined by Magnus Rattray (University of Manchester), to talk about 'Non-parametric modelling of gene expression in time and space'.
Sep 10, 2020
Magnus Rattray - Non-parametric modelling of gene expression in time and space
We were recently joined by Magnus Rattray (University of Manchester), to talk about 'Non-parametric modelling of gene expression in time and space'.
Sep 10, 2020
Magnus Rattray - Non-parametric modelling of gene expression in time and space
We were recently joined by Magnus Rattray (University of Manchester), to talk about 'Non-parametric modelling of gene expression in time and space'.
Sep 10, 2020
Magnus Rattray - Non-parametric modelling of gene expression in time and space
We were recently joined by Magnus Rattray (University of Manchester), to talk about 'Non-parametric modelling of gene expression in time and space'.
Sep 10, 2020
Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning
We were recently joined by Andreas Krause (ETH Zurich), to talk about 'Safe and Efficient Exploration in Reinforcement Learning'.
Aug 27, 2020
Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning
We were recently joined by Andreas Krause (ETH Zurich), to talk about 'Safe and Efficient Exploration in Reinforcement Learning'.
Aug 27, 2020
Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning
We were recently joined by Andreas Krause (ETH Zurich), to talk about 'Safe and Efficient Exploration in Reinforcement Learning'.
Aug 27, 2020
Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning
We were recently joined by Andreas Krause (ETH Zurich), to talk about 'Safe and Efficient Exploration in Reinforcement Learning'.
Aug 27, 2020
Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning
We were recently joined by Rahul Kidambi (Cornell University), to talk about 'MOReL: Model-Based Offline Reinforcement Learning'.
Aug 6, 2020
Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning
We were recently joined by Rahul Kidambi (Cornell University), to talk about 'MOReL: Model-Based Offline Reinforcement Learning'.
Aug 6, 2020
Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning
We were recently joined by Rahul Kidambi (Cornell University), to talk about 'MOReL: Model-Based Offline Reinforcement Learning'.
Aug 6, 2020
Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning
We were recently joined by Rahul Kidambi (Cornell University), to talk about 'MOReL: Model-Based Offline Reinforcement Learning'.
Aug 6, 2020
Arthur Gretton - Generalized Energy-Based Models
We were recently joined by Arthur Gretton (University College London), to talk about 'Generalized Energy-Based Models'.
Jul 30, 2020
Arthur Gretton - Generalized Energy-Based Models
We were recently joined by Arthur Gretton (University College London), to talk about 'Generalized Energy-Based Models'.
Jul 30, 2020
Arthur Gretton - Generalized Energy-Based Models
We were recently joined by Arthur Gretton (University College London), to talk about 'Generalized Energy-Based Models'.
Jul 30, 2020
Arthur Gretton - Generalized Energy-Based Models
We were recently joined by Arthur Gretton (University College London), to talk about 'Generalized Energy-Based Models'.
Jul 30, 2020
Gergely Neu - A unified view of entropy-regularized Markov decision processes
We were recently joined by Gergely Neu (Pompeu Fabra University), to talk about 'A unified view of entropy-regularized Markov decision processes'.
May 21, 2020
Gergely Neu - A unified view of entropy-regularized Markov decision processes
We were recently joined by Gergely Neu (Pompeu Fabra University), to talk about 'A unified view of entropy-regularized Markov decision processes'.
May 21, 2020
Gergely Neu - A unified view of entropy-regularized Markov decision processes
We were recently joined by Gergely Neu (Pompeu Fabra University), to talk about 'A unified view of entropy-regularized Markov decision processes'.
May 21, 2020
Gergely Neu - A unified view of entropy-regularized Markov decision processes
We were recently joined by Gergely Neu (Pompeu Fabra University), to talk about 'A unified view of entropy-regularized Markov decision processes'.
May 21, 2020
Products
Resources
Get in touch
© Secondmind 2025
Products
Resources
Get in touch
© Secondmind 2025
Products
Resources
Get in touch
© Secondmind 2025
Products
Resources
Get in touch
© Secondmind 2025