The NeurIPS conference stands at the forefront of AI research. This year, we are thrilled to share that our research team members have contributed to the following papers*.
Conference main track
- Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning Mathias Lechner, Lianhao Yin, Tim Seyde, Tsun-Hsuan Wang, Wei Xiao, Ramin Hasani, Joshua Rountree, Daniela Rus
- On the Size and Approximation Error of Distilled Datasets Alaa Maalouf, Murad Tukan, Noel Loo, Ramin Hasani, Mathias Lechner, Daniela Rus
- Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees Đorđe Žikelić, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A Henzinger
- Convolutional State Space Models for Long-Range Spatiotemporal Modeling Jimmy T.H. Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon
- Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions Stefano Massaroli, Michael Poli, Daniel Y Fu, Hermann Kumbong, Rom Nishijima Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Re, Stefano Ermon, Yoshua Bengio
- HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution Eric Nguyen, Michael Poli, Marjan Faizi, Armin W Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Re, Stephen Baccus
- Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio
- Learning Efficient Surrogate Dynamic Models with Graph Spline Networks Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park
- DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim, Andrew Everett Spielberg, Joshua B. Tenenbaum, Chuang Gan, Daniela Rus
- Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
Workshop papers
- Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao, Yutong Ban, Alexander Amini, Guy Rosman, Sertac Karaman, Daniela Rus
- How Structured Data Guides Feature Learning: A Case Study of the Parity Problem Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, Denny Wu
- Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control Neehal Tumma, Mathias Lechner, Noel Loo, Ramin Hasani, Daniela Rus
- Exploring Modern Evolution Strategies in Portfolio Optimization at OPT
* Disclaimer: Liquid research team members (highlighted in bold and italic) have co-authored these papers at their respective organizations independently of the work that they do at Liquid AI, Inc.
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