Joshua M. Susskind

According to our database, Joshua M. Susskind authored at least 53 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How Far Are We from Intelligent Visual Deductive Reasoning?

Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly

CoRR, 2024

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization.

Yuhang Zang, Hanlin Goh, Josh M. Susskind, Chen Huang

CoRR, 2024

Scalable Pre-training of Large Autoregressive Image Models.

Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin

CoRR, 2024

2023

LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures.

Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin

CoRR, 2023

Generating Molecular Conformer Fields.

Yuyang Wang, Ahmed A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

CoRR, 2023

Vanishing Gradients in Reinforcement Finetuning of Language Models.

Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin

CoRR, 2023

What Algorithms can Transformers Learn? A Study in Length Generalization.

Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Josh M. Susskind, Samy Bengio, Preetum Nakkiran

CoRR, 2023

Matryoshka Diffusion Models.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Josh M. Susskind, Navdeep Jaitly

CoRR, 2023

When can transformers reason with abstract symbols?

Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind

CoRR, 2023

Adaptivity and Modularity for Efficient Generalization Over Task Complexity.

Samira Abnar, Omid Saremi, Laurent Dinh, Shantel Wilson, Miguel Ángel Bautista, Chen Huang, Vimal Thilak, Etai Littwin, Jiatao Gu, Josh M. Susskind, Samy Bengio

CoRR, 2023

Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today?

Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing

CoRR, 2023

Generative Modeling with Phase Stochastic Bridges.

Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Josh M. Susskind, Shuangfei Zhai

CoRR, 2023

Boolformer: Symbolic Regression of Logic Functions with Transformers.

Stéphane d'Ascoli, Samy Bengio, Josh M. Susskind, Emmanuel Abbe

CoRR, 2023

Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation.

Ali Mousavi, Xin Zhan, He Bai, Peng Shi, Theodoros Rekatsinas, Benjamin Han, Yunyao Li, Jeffrey Pound, Josh M. Susskind, Natalie Schluter, Ihab F. Ilyas, Navdeep Jaitly

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

BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Josh M. Susskind

CoRR, 2023

Manifold Diffusion Fields.

Ahmed A. Elhag, Joshua M. Susskind, Miguel Ángel Bautista

CoRR, 2023

Learning Controllable 3D Diffusion Models from Single-view Images.

Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind

CoRR, 2023

Transformers learn through gradual rank increase.

Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model.

Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stabilizing Transformer Training by Preventing Attention Entropy Collapse.

Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind

Proceedings of the International Conference on Machine Learning, 2023

NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion.

Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M. Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi

Proceedings of the International Conference on Machine Learning, 2023

Diffusion Probabilistic Fields.

Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista

Proceedings of the Eleventh International Conference on Learning Representations, 2023

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors.

Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon.

Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind

CoRR, 2022

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

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

CoRR, 2022

Fast and Explicit Neural View Synthesis.

Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 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

Learning Representation from Neural Fisher Kernel with Low-rank Approximation.

Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind

Proceedings of the Tenth International Conference on Learning Representations, 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

Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks.

Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua M. Susskind

CoRR, 2021

Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks.

Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang

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

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning.

Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Proceedings of the 38th International Conference on Machine Learning, 2021

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding.

Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Ángel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Unconstrained Scene Generation with Locally Conditioned Radiance Fields.

Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

MetricOpt: Learning To Optimize Black-Box Evaluation Metrics.

Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 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

Equivariant Neural Rendering.

Emilien Dupont, Miguel Ángel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh M. Susskind, Qi Shan

CoRR, 2020

Collegial Ensembles.

Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Equivariant Neural Rendering.

Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh M. Susskind, Qi Shan

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking.

Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind

CoRR, 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

2013

Modeling Natural Images Using Gated MRFs.

Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton

IEEE Trans. Pattern Anal. Mach. Intell., 2013

2011

Modeling the joint density of two images under a variety of transformations.

Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

On deep generative models with applications to recognition.

Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2008

Analysis-by-Synthesis by Learning to Invert Generative Black Boxes.

Vinod Nair, Joshua M. Susskind, Geoffrey E. Hinton

Proceedings of the Artificial Neural Networks, 2008