David Sussillo

35 papers A* 9Journal 21Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Enabling Advanced Interactions through Closed-loop Control of Motor Unit Activity After Tetraplegia. UIST (Adjunct Volume) Dailyn Despradel Despradel, Max Murphy, Luigi Borda, Nikhil Verma, Prakarsh Yadav, Jenn Shanahan, Najja Marshall, Emanuele Formento, Mario Bräcklein, Jun Ye, Peter Walkington, Rishi Rajalingham, David Sussillo, Stephanie Naufel, Diego Adrian Gutnisky, Jennifer L. Collinger, Douglas J. Weber
2023	J	`jnl`	Analyzing Populations of Neural Networks via Dynamical Model Embedding. CoRR Jordan Cotler, Kai Sheng Tai, Felipe Hernández, Blake Elias, David Sussillo
2023	J	`jnl`	One dimensional approximations of neuronal dynamics reveal computational strategy. PLoS Comput. Biol. Connor Brennan, Adeeti Aggarwal, Rui Pei, David Sussillo, Alex Proekt
2022	J	`jnl`	Recurrent Connections in the Primate Ventral Visual Stream Mediate a Trade-Off Between Task Performance and Network Size During Core Object Recognition. Neural Comput. Aran Nayebi, Javier Sagastuy-Breña, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2022	J	`jnl`	Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR 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
2021	A*	`conf`	Reverse engineering learned optimizers reveals known and novel mechanisms. NeurIPS Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein
2021	A*	`conf`	Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. NeurIPS Jimmy T. H. Smith, Scott W. Linderman, David Sussillo
2021	J	`jnl`	Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. CoRR Jimmy T. H. Smith, Scott W. Linderman, David Sussillo
2021	A*	`conf`	The geometry of integration in text classification RNNs. ICLR Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
2020	A*	`conf`	How recurrent networks implement contextual processing in sentiment analysis. ICML Niru Maheswaranathan, David Sussillo
2020	J	`jnl`	How recurrent networks implement contextual processing in sentiment analysis. CoRR Niru Maheswaranathan, David Sussillo
2020	A*	`conf`	Organizing recurrent network dynamics by task-computation to enable continual learning. NeurIPS Lea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo
2020	J	`jnl`	Reverse engineering learned optimizers reveals known and novel mechanisms. CoRR Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein
2020	J	`jnl`	The geometry of integration in text classification RNNs. CoRR Kyle Aitken, Vinay V. Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan
2019	A*	`conf`	Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. NeurIPS Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	J	`jnl`	Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. CoRR Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	A*	`conf`	Universality and individuality in neural dynamics across large populations of recurrent networks. NeurIPS Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2019	J	`jnl`	Universality and individuality in neural dynamics across large populations of recurrent networks. CoRR Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo
2018	—	`conf`	A Dataset and Architecture for Visual Reasoning with a Working Memory. ECCV (10) Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo
2018	J	`jnl`	A dataset and architecture for visual reasoning with a working memory. CoRR Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo
2018	J	`jnl`	FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks. J. Open Source Softw. Matthew D. Golub, David Sussillo
2018	—	`conf`	Recurrent Segmentation for Variable Computational Budgets. CVPR Workshops Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens
2018	A*	`conf`	Task-Driven Convolutional Recurrent Models of the Visual System. NeurIPS Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2018	J	`jnl`	Task-Driven Convolutional Recurrent Models of the Visual System. CoRR Aran Nayebi, Daniel Bear, Jonas Kubilius, Kohitij Kar, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
2017	—	`conf`	Capacity and Trainability in Recurrent Neural Networks. ICLR (Poster) Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
2017	A*	`conf`	Input Switched Affine Networks: An RNN Architecture Designed for Interpretability. ICML Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein, Jan Chorowski, David Sussillo
2017	J	`jnl`	Recurrent Segmentation for Variable Computational Budgets. CoRR Lane McIntosh, David Sussillo, Niru Maheswaranathan, Jonathon Shlens
2016	—	`conf`	An Online Sequence-to-Sequence Model Using Partial Conditioning. NIPS Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio
2016	J	`jnl`	Capacity and Trainability in Recurrent Neural Networks. CoRR Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
2016	J	`jnl`	Intelligible Language Modeling with Input Switched Affine Networks. CoRR Jakob N. Foerster, Justin Gilmer, Jan Chorowski, Jascha Sohl-Dickstein, David Sussillo
2016	J	`jnl`	LFADS - Latent Factor Analysis via Dynamical Systems. CoRR David Sussillo, Rafal Józefowicz, L. F. Abbott, Chethan Pandarinath
2014	J	`jnl`	Information Systems Opportunities in Brain-Machine Interface Decoders. Proc. IEEE Jonathan C. Kao, Sergey D. Stavisky, David Sussillo, Paul Nuyujukian, Krishna V. Shenoy
2014	J	`jnl`	Random Walks: Training Very Deep Nonlinear Feed-Forward Networks with Smart Initialization. CoRR David Sussillo
2013	J	`jnl`	Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks. Neural Comput. David Sussillo, Omri Barak
2004	J	`jnl`	Spectrogram Analysis of Genomes. EURASIP J. Adv. Signal Process. David Sussillo, Anshul Kundaje, Dimitris Anastassiou