Stanford AI Lab Showcases Research at NeurIPS 2021
The Stanford Artificial Intelligence Laboratory (SAIL) has announced its comprehensive participation in the thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021, held virtually from December 6th to 14th. The laboratory is presenting a diverse array of research papers across the main conference, the Datasets and Benchmarks track, and various specialized workshops. Key contributions include studies on improving neural network compositionality, reverse-engineering recurrent neural networks using Jacobian switching linear dynamical systems, and developing compositional transformers for scene generation. Additionally, SAIL members are serving as co-organizers for several workshops scheduled for mid-December. The announcement provides direct links to academic papers, video presentations, and code repositories, encouraging the broader AI community to engage with Stanford's latest advancements in generative models, interpretability, and efficient deep learning techniques. This collection highlights significant technical progress in areas such as sequence modeling, emergent communication, and data efficiency, reflecting the lab's active role in shaping contemporary artificial intelligence research.
Wire timeline
Stanford AI Lab Showcases Research at NeurIPS 2021
The Stanford Artificial Intelligence Laboratory (SAIL) has announced its comprehensive participation in the thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021, held virtually from December 6th to 14th. The laboratory is presenting a diverse array of research papers across the main conference, the Datasets and Benchmarks track, and various specialized workshops. Key contributions include studies on improving neural network compositionality, reverse-engineering recurrent neural networks using Jacobian switching linear dynamical systems, and developing compositional transformers for scene generation. Additionally, SAIL members are serving as co-organizers for several workshops scheduled for mid-December. The announcement provides direct links to academic papers, video presentations, and code repositories, encouraging the broader AI community to engage with Stanford's latest advancements in generative models, interpretability, and efficient deep learning techniques. This collection highlights significant technical progress in areas such as sequence modeling, emergent communication, and data efficiency, reflecting the lab's active role in shaping contemporary artificial intelligence research.
The Stanford AI Lab Blog