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ORCIDChristian Schröder de Witt
Christian A. Schröder de Witt
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2020 – today
- 2024
[c24]Linas Nasvytis, Kai Sandbrink, Jakob N. Foerster, Tim Franzmeyer, Christian Schröder de Witt:
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection. AAMAS 2024: 1445-1453- [c23]Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster:
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. AAMAS 2024: 2444-2446 - [c22]Tim Franzmeyer, Stephen Marcus McAleer, João F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schröder de Witt:
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks. ICLR 2024 - [c21]Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster:
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. ICML 2024 - [c20]Mattie Fellows, Brandon Kaplowitz, Christian Schröder de Witt, Shimon Whiteson:
Bayesian Exploration Networks. ICML 2024 - [c19]Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Christian Schröder de Witt:
Unelicitable Backdoors via Cryptographic Transformer Circuits. NeurIPS 2024 - [c18]Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip Torr, Lewis Hammond, Christian Schröder de Witt:
Secret Collusion among AI Agents: Multi-Agent Deception via Steganography. NeurIPS 2024 - [c17]Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster:
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. NeurIPS 2024 - [i44]Jake Levi, Chris Lu, Timon Willi, Christian Schröder de Witt, Jakob N. Foerster:
The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games. CoRR abs/2402.01088 (2024) - [i43]Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip H. S. Torr, Lewis Hammond, Christian Schröder de Witt:
Secret Collusion Among Generative AI Agents. CoRR abs/2402.07510 (2024) - [i42]Linas Nasvytis, Kai Sandbrink, Jakob N. Foerster, Tim Franzmeyer, Christian Schröder de Witt:
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection. CoRR abs/2404.07099 (2024) - [i41]Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi
, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster:
Near to Mid-term Risks and Opportunities of Open Source Generative AI. CoRR abs/2404.17047 (2024) - [i40]Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Aaron Purewal, Botos Csaba, Fabro Steibel, Fazel Keshtkar, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Thomas Jackson, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster:
Risks and Opportunities of Open-Source Generative AI. CoRR abs/2405.08597 (2024) - [i39]Samuel Sokota, Dylan Sam, Christian Schröder de Witt, Spencer Compton, Jakob N. Foerster, J. Zico Kolter:
Computing Low-Entropy Couplings for Large-Support Distributions. CoRR abs/2405.19540 (2024) - [i38]Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Charlie Rogers-Smith, Jeffrey Ladish, Christian Schröder de Witt:
Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits. CoRR abs/2406.02619 (2024) - [i37]Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schröder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung:
IDs for AI Systems. CoRR abs/2406.12137 (2024) - [i36]Yohan Mathew, Ollie Matthews, Robert McCarthy, Joan Velja, Christian Schröder de Witt, Dylan Cope, Nandi Schoots:
Hidden in Plain Text: Emergence & Mitigation of Steganographic Collusion in LLMs. CoRR abs/2410.03768 (2024) - [i35]Georgia Channing, Juil Sock, Ronald Clark, Philip Torr, Christian Schröder de Witt:
Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap. CoRR abs/2410.07436 (2024) - [i34]Constantin Venhoff, Anisoara Calinescu, Philip Torr, Christian Schröder de Witt:
SAGE: Scalable Ground Truth Evaluations for Large Sparse Autoencoders. CoRR abs/2410.07456 (2024) - [i33]Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt:
Efficient Dictionary Learning with Switch Sparse Autoencoders. CoRR abs/2410.08201 (2024) - [i32]Kumud Lakara, Juil Sock, Christian Rupprecht, Philip Torr, John Collomosse, Christian Schröder de Witt:
MAD-Sherlock: Multi-Agent Debates for Out-of-Context Misinformation Detection. CoRR abs/2410.20140 (2024) - [i31]Jon Chun, Christian Schröder de Witt, Katherine Elkins:
Comparative Global AI Regulation: Policy Perspectives from the EU, China, and the US. CoRR abs/2410.21279 (2024) - [i30]Wenjie Li, Jiawei Li, Christian Schröder de Witt, Ameya Prabhu, Amartya Sanyal:
Delta-Influence: Unlearning Poisons via Influence Functions. CoRR abs/2411.13731 (2024) - [i29]Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Markian Rybchuk, Philip H. S. Torr, Ivan Laptev, Fabio Pizzati, Ronald Clark, Christian Schröder de Witt:
MALT: Improving Reasoning with Multi-Agent LLM Training. CoRR abs/2412.01928 (2024) - 2023
- [c16]Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson:
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. ICLR 2023 - [c15]Christian Schröder de Witt, Samuel Sokota, J. Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier:
Perfectly Secure Steganography Using Minimum Entropy Coupling. ICLR 2023 - [i28]Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson:
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning. CoRR abs/2303.10733 (2023) - [i27]Mattie Fellows, Brandon Kaplowitz, Christian Schröder de Witt, Shimon Whiteson:
Bayesian Exploration Networks. CoRR abs/2308.13049 (2023) - [i26]Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster:
JaxMARL: Multi-Agent RL Environments in JAX. CoRR abs/2311.10090 (2023) - 2022
- [c14]Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood:
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS 2022: 8392-8412 - [c13]Jakub Grudzien Kuba, Christian A. Schröder de Witt, Jakob N. Foerster:
Mirror Learning: A Unifying Framework of Policy Optimisation. ICML 2022: 7825-7844 - [c12]Christopher Lu, Timon Willi, Christian A. Schröder de Witt, Jakob N. Foerster:
Model-Free Opponent Shaping. ICML 2022: 14398-14411 - [c11]Darius Muglich, Luisa M. Zintgraf, Christian A. Schröder de Witt, Shimon Whiteson, Jakob N. Foerster:
Generalized Beliefs for Cooperative AI. ICML 2022: 16062-16082 - [c10]Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster:
Communicating via Markov Decision Processes. ICML 2022: 20314-20328 - [c9]Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster:
Discovered Policy Optimisation. NeurIPS 2022 - [c8]Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster:
Equivariant Networks for Zero-Shot Coordination. NeurIPS 2022 - [i25]Jakub Grudzien Kuba, Christian Schröder de Witt, Jakob N. Foerster:
Mirror Learning: A Unifying Framework of Policy Optimisation. CoRR abs/2201.02373 (2022) - [i24]Yoshua Bengio, Prateek Gupta, Dylan R. Radovic, Maarten Scholl, Andrew Williams, Christian Schröder de Witt, Tianyu Zhang, Yang Zhang:
(Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment. CoRR abs/2205.00666 (2022) - [i23]Christopher Lu, Timon Willi, Christian Schröder de Witt, Jakob N. Foerster:
Model-Free Opponent Shaping. CoRR abs/2205.01447 (2022) - [i22]Christian Schröder de Witt:
Biological Evolution and Genetic Algorithms: Exploring the Space of Abstract Tile Self-Assembly. CoRR abs/2205.15311 (2022) - [i21]Darius Muglich, Luisa M. Zintgraf, Christian Schröder de Witt, Shimon Whiteson, Jakob N. Foerster:
Generalized Beliefs for Cooperative AI. CoRR abs/2206.12765 (2022) - [i20]Tim Franzmeyer, João F. Henriques, Jakob N. Foerster, Philip H. S. Torr, Adel Bibi, Christian Schröder de Witt:
Illusionary Attacks on Sequential Decision Makers and Countermeasures. CoRR abs/2207.10170 (2022) - [i19]Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster:
Discovered Policy Optimisation. CoRR abs/2210.05639 (2022) - [i18]Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster:
Equivariant Networks for Zero-Shot Coordination. CoRR abs/2210.12124 (2022) - [i17]Christian Schröder de Witt, Samuel Sokota, J. Zico Kolter, Jakob N. Foerster, Martin Strohmeier:
Perfectly Secure Steganography Using Minimum Entropy Coupling. CoRR abs/2210.14889 (2022) - [i16]Dylan R. Radovic, Lucas Kruitwagen, Christian Schröder de Witt, Ben Caldecott, Shane Tomlinson, Mark Workman:
Revealing Robust Oil and Gas Company Macro-Strategies using Deep Multi-Agent Reinforcement Learning. CoRR abs/2211.11043 (2022) - 2021
- [c7]Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski:
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery. AAAI 2021: 14902-14910 - [c6]Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha:
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning. ICML 2021: 4596-4606 - [c5]Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson:
FACMAC: Factored Multi-Agent Centralised Policy Gradients. NeurIPS 2021: 12208-12221 - [i15]Eltayeb Ahmed, Luisa M. Zintgraf, Christian A. Schröder de Witt, Nicolas Usunier:
A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings. CoRR abs/2104.08492 (2021) - [i14]Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster:
Implicit Communication as Minimum Entropy Coupling. CoRR abs/2107.08295 (2021) - [i13]Christian Schröder de Witt, Yongchao Huang, Philip H. S. Torr, Martin Strohmeier:
Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI-NIDS. CoRR abs/2111.12197 (2021) - 2020
- [j1]Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson:
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. J. Mach. Learn. Res. 21: 178:1-178:51 (2020) - [i12]Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, Shimon Whiteson:
Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control. CoRR abs/2003.06709 (2020) - [i11]Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson:
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. CoRR abs/2003.08839 (2020) - [i10]Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin:
Simulation-Based Inference for Global Health Decisions. CoRR abs/2005.07062 (2020) - [i9]Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha:
AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning. CoRR abs/2006.04222 (2020) - [i8]Christian Schröder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip H. S. Torr, Mingfei Sun, Shimon Whiteson:
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge? CoRR abs/2011.09533 (2020) - [i7]Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski:
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery. CoRR abs/2012.09670 (2020)
2010 – 2019
- 2019
- [c4]Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob N. Foerster, Shimon Whiteson:
The StarCraft Multi-Agent Challenge. AAMAS 2019: 2186-2188 - [c3]Christian Schröder de Witt, Jakob N. Foerster, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson:
Multi-Agent Common Knowledge Reinforcement Learning. NeurIPS 2019: 9924-9935 - [i6]Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob N. Foerster, Shimon Whiteson:
The StarCraft Multi-Agent Challenge. CoRR abs/1902.04043 (2019) - [i5]Christian Schröder de Witt, Thomas Hornigold:
Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem. CoRR abs/1905.07366 (2019) - [i4]Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth, Philip H. S. Torr, Yee Whye Teh, Atilim Günes Baydin:
Hijacking Malaria Simulators with Probabilistic Programming. CoRR abs/1905.12432 (2019) - [i3]Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Günes Baydin, Bradley Gram-Hansen, Christian Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood:
Amortized Rejection Sampling in Universal Probabilistic Programming. CoRR abs/1910.09056 (2019) - 2018
- [c2]Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson:
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. ICML 2018: 4292-4301 - [i2]Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson:
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning. CoRR abs/1803.11485 (2018) - [i1]Jakob N. Foerster, Christian A. Schröder de Witt, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson:
Multi-Agent Common Knowledge Reinforcement Learning. CoRR abs/1810.11702 (2018) - 2014
- [c1]Christian Schröder de Witt, Vladimir Zamdzhiev:
The ZX calculus is incomplete for quantum mechanics. QPL 2014: 285-292
Coauthor Index
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