David Sussillo

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 30

Top Topics

Dynamical Systems

Text Classification

Recurrent Neural Networks

Top Venues

Publications

Jordan Cotler, Kai Sheng Tai, Felipe Hernández, Blake Elias, David Sussillo
Analyzing Populations of Neural Networks via Dynamical Model Embedding. CoRR (2023)
Connor Brennan, Adeeti Aggarwal, Rui Pei, David Sussillo, Alex Proekt
One dimensional approximations of neuronal dynamics reveal computational strategy. PLoS Comput. Biol. 19 (1) (2023)
Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Comput. 34 (8) (2022)
Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR (2022)
Jimmy T. H. Smith, Scott W. Linderman, David Sussillo
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. CoRR (2021)
Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
The geometry of integration in text classification RNNs. ICLR (2021)
Jimmy T. H. Smith, Scott W. Linderman, David Sussillo
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. NeurIPS (2021)
Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein
Reverse engineering learned optimizers reveals known and novel mechanisms. NeurIPS (2021)
Lea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo
Organizing recurrent network dynamics by task-computation to enable continual learning. NeurIPS (2020)
Niru Maheswaranathan, David Sussillo
How recurrent networks implement contextual processing in sentiment analysis. CoRR (2020)
Kyle Aitken, Vinay V. Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
The geometry of integration in text classification RNNs. CoRR (2020)
Niru Maheswaranathan, David Sussillo
How recurrent networks implement contextual processing in sentiment analysis. ICML (2020)
Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein
Reverse engineering learned optimizers reveals known and novel mechanisms. CoRR (2020)
Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
Universality and individuality in neural dynamics across large populations of recurrent networks. NeurIPS (2019)
Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. CoRR (2019)
Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
Universality and individuality in neural dynamics across large populations of recurrent networks. CoRR (2019)
Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. NeurIPS (2019)
Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo
A dataset and architecture for visual reasoning with a working memory. CoRR (2018)
Matthew D. Golub, David Sussillo
FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks. J. Open Source Softw. 3 (31) (2018)
Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo
A Dataset and Architecture for Visual Reasoning with a Working Memory. ECCV (10) (2018)
Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
Task-Driven Convolutional Recurrent Models of the Visual System. CoRR (2018)
Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens
Recurrent Segmentation for Variable Computational Budgets. CVPR Workshops (2018)
Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. Yamins
Task-Driven Convolutional Recurrent Models of the Visual System. NeurIPS (2018)
Lane McIntosh, David Sussillo, Niru Maheswaranathan, Jonathon Shlens
Recurrent Segmentation for Variable Computational Budgets. CoRR (2017)
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
Capacity and Trainability in Recurrent Neural Networks. ICLR (Poster) (2017)
Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein, Jan Chorowski, David Sussillo
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability. ICML (2017)
David Sussillo, Rafal Józefowicz, L. F. Abbott, Chethan Pandarinath
LFADS - Latent Factor Analysis via Dynamical Systems. CoRR (2016)
Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio
An Online Sequence-to-Sequence Model Using Partial Conditioning. NIPS (2016)
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
Capacity and Trainability in Recurrent Neural Networks. CoRR (2016)
Jakob N. Foerster, Justin Gilmer, Jan Chorowski, Jascha Sohl-Dickstein, David Sussillo
Intelligible Language Modeling with Input Switched Affine Networks. CoRR (2016)
Jonathan C. Kao, Sergey D. Stavisky, David Sussillo, Paul Nuyujukian, Krishna V. Shenoy
Information Systems Opportunities in Brain-Machine Interface Decoders. Proc. IEEE 102 (5) (2014)
David Sussillo
Random Walks: Training Very Deep Nonlinear Feed-Forward Networks with Smart Initialization. CoRR (2014)
David Sussillo, Omri Barak
Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks. Neural Comput. 25 (3) (2013)
David Sussillo, Anshul Kundaje, Dimitris Anastassiou
Spectrogram Analysis of Genomes. EURASIP J. Adv. Signal Process. 2004 (1) (2004)