David Ding

According to our database, David Ding authored at least 12 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices.

David Ding, Ivan Carvalho, Ramon Lawrence

Proceedings of the 12th International Conference on Sensor Networks, 2023

Know your audience: specializing grounded language models with listener subtraction.

Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2022

Know your audience: specializing grounded language models with the game of Dixit.

Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen

CoRR, 2022

Perceiver IO: A General Architecture for Structured Inputs & Outputs.

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

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Attention over Learned Object Embeddings Enables Complex Visual Reasoning.

David Ding, Felix Hill, Adam Santoro, Malcolm Reynolds, Matt M. Botvinick

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Evaluation of Durability of Transparent Graphene Electrodes Fabricated on Different Flexible Substrates for Chronic In Vivo Experiments.

David Ding, Yichen Lu, Ruoyu Zhao, Xin Liu, Chawina De-Eknamkul, Chi Ren, Armaghan Mehrsa, Takaki Komiyama, Duygu Kuzum

IEEE Trans. Biomed. Eng., 2020

Object-based attention for spatio-temporal reasoning: Outperforming neuro-symbolic models with flexible distributed architectures.

David Ding, Felix Hill, Adam Santoro, Matt M. Botvinick

CoRR, 2020

2019

Adapting Behaviour for Learning Progress.

Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero

CoRR, 2019

OpenSpiel: A Framework for Reinforcement Learning in Games.

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

CoRR, 2019

Decoding ECoG High Gamma Power from Cellular Calcium Response using Transparent Graphene Microelectrodes.

Xin Liu, Chi Ren, Yichen Lu, Ryoma Hattori, Yuhan Shi, Ruoyu Zhao, David Ding, Takaki Komiyama, Duygu Kuzum

Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

2017

Deep Lattice Networks and Partial Monotonic Functions.

Seungil You, David Ding, Kevin Robert Canini, Jan Pfeifer, Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Fostering Digital Innovation through Inter-Organizational Collaboration between Incumbent Firms and Start-UPS.

Nihal Islam, Peter Buxmann, David Ding

Proceedings of the 25th European Conference on Information Systems, 2017