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News and Updates
- Graph Metanetworks for Processing Diverse Neural Architectures
By Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, and James Lucas
Graph Metanetworks for Processing Diverse Neural Architectures
- COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
By Anne Harrington, Vasha DuTell, Mark Hamilton, Ayush Tewari, Simon Stent, and 2 others
COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
- Leave-one-out Distinguishability in Machine Learning
By Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, and Reza Shokri
Leave-one-out Distinguishability in Machine Learning
- Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
By Neehal Tumma, Mathias Lechner, Noel Loo, Ramin Hasani, and Daniela Rus
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
- How Structured Data Guides Feature Learning: A Case Study of the Parity Problem
By Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, and Denny Wu
How Structured Data Guides Feature Learning: A Case Study of the Parity Problem
- Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models
By Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao, Yutong Ban, Alexander Amini, and 3 others
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models
- Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
By Neehal Tumma, Mathias Lechner, Noel Loo, Ramin Hasani, and Daniela Rus
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
- Exploring Modern Evolution Strategies in Portfolio Optimization
By Ramin Hasani, Etan A Ehsanfar, Greg A Banis, Rusty Bealer, and Amir Soroush Ahmadi
Exploring Modern Evolution Strategies in Portfolio Optimization
- Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
By Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Wang, Wei Xiao, and 3 others
Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
- On the Size and Approximation Error of Distilled Datasets
By Alaa Maalouf, Murad Tukan, Noel Loo, Ramin Hasani, Mathias Lechner, and 1 other
On the Size and Approximation Error of Distilled Datasets
- Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
By Đorđe Žikelić, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, and Thomas A Henzinger
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees
- Convolutional State Space Models for Long-Range Spatiotemporal Modeling
By Jimmy T.H. Smith, Shalini De Mello, Jan Kautz, Scott Linderman, and Wonmin Byeon
Convolutional State Space Models for Long-Range Spatiotemporal Modeling
- HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
By Eric Nguyen, Michael Poli, Marjan Faizi, Armin W Thomas, Michael Wornow, and 8 others
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
- Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
By Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, and 2 others
Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
- Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
By Stefano Massaroli, Michael Poli, Daniel Y Fu, Hermann Kumbong, Rom Nishijima Parnichkun, and 9 others
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
- DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
By Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim, and 4 others
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models
- Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
By Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, and Jinkyoo Park
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
- Expressive Sign Equivariant Networks for Spectral Geometric Learning
By Derek Lim, Joshua Robinson, Stefanie Jegelka, and Haggai Maron
Expressive Sign Equivariant Networks for Spectral Geometric Learning