Walter Talbott

According to our database, Walter Talbott authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning.

Yao-Hung Hubert Tsai, Walter Talbott, Jian Zhang

CoRR, 2024

2023

Large Language Models as Generalizable Policies for Embodied Tasks.

Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Walter Talbott, Katherine Metcalf, Natalie Mackraz, R. Devon Hjelm, Alexander Toshev

CoRR, 2023

Value function estimation using conditional diffusion models for control.

Bogdan Mazoure, Walter Talbott, Miguel Ángel Bautista, R. Devon Hjelm, Alexander Toshev, Joshua M. Susskind

CoRR, 2023

TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation.

David Berthelot, Arnaud Autef, Jierui Lin, Dian Ang Yap, Shuangfei Zhai, Siyuan Hu, Daniel Zheng, Walter Talbott, Eric Gu

CoRR, 2023

2022

Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation.

Martin Bertran Lopez, Walter Talbott, Nitish Srivastava, Joshua M. Susskind

CoRR, 2022

GAUDI: A Neural Architect for Immersive 3D Scene Generation.

Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Regularized Training of Nearest Neighbor Language Models.

Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, 2022

Position Prediction as an Effective Pretraining Strategy.

Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y. Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind

Proceedings of the International Conference on Machine Learning, 2022

Efficient Representation Learning via Adaptive Context Pooling.

Chen Huang, Walter Talbott, Navdeep Jaitly, Joshua M. Susskind

Proceedings of the International Conference on Machine Learning, 2022

2021

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models.

Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Josh M. Susskind

CoRR, 2021

An Attention Free Transformer.

Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh M. Susskind

CoRR, 2021

On the generalization of learning-based 3D reconstruction.

Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

2020

Set Distribution Networks: a Generative Model for Sets of Images.

Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Carlos Guestrin, Josh M. Susskind

CoRR, 2020

2019

Adversarial Fisher Vectors for Unsupervised Representation Learning.

Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment.

Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind

Proceedings of the 36th International Conference on Machine Learning, 2019