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2020 – today
- 2023
[c7]Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen:
Know your audience: specializing grounded language models with listener subtraction. EACL 2023: 3866-3893- [c6]David Ding, Ivan Carvalho, Ramon Lawrence:
Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices. SENSORNETS 2023: 23-31 - [i7]David Ding, Ivan Carvalho, Ramon Lawrence:
Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices. CoRR abs/2302.03085 (2023) - 2022
- [c5]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - [i6]Aaditya K. Singh, David Ding, Andrew M. Saxe
, Felix Hill, Andrew K. Lampinen:
Know your audience: specializing grounded language models with the game of Dixit. CoRR abs/2206.08349 (2022) - 2021
- [c4]David Ding, Felix Hill, Adam Santoro, Malcolm Reynolds, Matt M. Botvinick:
Attention over Learned Object Embeddings Enables Complex Visual Reasoning. NeurIPS 2021: 9112-9124 - [i5]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - 2020
- [j1]David Ding, Yichen Lu, Ruoyu Zhao, Xin Liu, Chawina De-Eknamkul, Chi Ren, Armaghan Mehrsa, Takaki Komiyama, Duygu Kuzum:
Evaluation of Durability of Transparent Graphene Electrodes Fabricated on Different Flexible Substrates for Chronic In Vivo Experiments. IEEE Trans. Biomed. Eng. 67(11): 3203-3210 (2020) - [i4]David Ding, Felix Hill, Adam Santoro, Matt M. Botvinick:
Object-based attention for spatio-temporal reasoning: Outperforming neuro-symbolic models with flexible distributed architectures. CoRR abs/2012.08508 (2020)
2010 – 2019
- 2019
- [c3]Xin Liu, Chi Ren, Yichen Lu, Ryoma Hattori, Yuhan Shi, Ruoyu Zhao, David Ding, Takaki Komiyama, Duygu Kuzum:
Decoding ECoG High Gamma Power from Cellular Calcium Response using Transparent Graphene Microelectrodes. NER 2019: 710-713 - [i3]Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis:
OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR abs/1908.09453 (2019) - [i2]Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero:
Adapting Behaviour for Learning Progress. CoRR abs/1912.06910 (2019) - 2017
- [c2]Nihal Islam, Peter Buxmann, David Ding:
Fostering Digital Innovation through Inter-Organizational Collaboration between Incumbent Firms and Start-UPS. ECIS 2017: 67 - [c1]Seungil You, David Ding, Kevin Robert Canini, Jan Pfeifer, Maya R. Gupta:
Deep Lattice Networks and Partial Monotonic Functions. NIPS 2017: 2981-2989 - [i1]Seungil You, David Ding, Kevin Robert Canini, Jan Pfeifer, Maya R. Gupta:
Deep Lattice Networks and Partial Monotonic Functions. CoRR abs/1709.06680 (2017)
Coauthor Index
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