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ORCIDJoshua M. Susskind
Josh M. Susskind
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Journal Articles
- 2025
[j3]Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai:
Improving GFlowNets for Text-to-Image Diffusion Alignment. Trans. Mach. Learn. Res. 2025 (2025)- 2024
- [j2]Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind:
The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods. Trans. Mach. Learn. Res. 2024 (2024) - 2013
- [j1]Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton:
Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2206-2222 (2013)
Conference and Workshop Papers
- 2025
- [c43]Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai:
Denoising Autoregressive Transformers for Scalable Text-to-Image Generation. ICLR 2025 - 2024
- [c42]Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind:
Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images. 3DV 2024: 685-696 - [c41]Ali Mousavi, Xin Zhan, He Bai, Peng Shi, Theodoros Rekatsinas, Benjamin Han, Yunyao Li, Jeffrey Pound, Joshua M. Susskind, Natalie Schluter, Ihab F. Ilyas, Navdeep Jaitly:
Construction of Paired Knowledge Graph - Text Datasets Informed by Cyclic Evaluation. LREC/COLING 2024: 3782-3803 - [c40]Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing:
Pseudo-Generalized Dynamic View Synthesis from a Video. ICLR 2024 - [c39]Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind:
When can transformers reason with abstract symbols? ICLR 2024 - [c38]Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai:
Generative Modeling with Phase Stochastic Bridge. ICLR 2024 - [c37]Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista:
Manifold Diffusion Fields. ICLR 2024 - [c36]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly:
Matryoshka Diffusion Models. ICLR 2024 - [c35]Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin:
Vanishing Gradients in Reinforcement Finetuning of Language Models. ICLR 2024 - [c34]Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin:
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. ICLR 2024 - [c33]Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang:
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. ICLR 2024 - [c32]Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran:
What Algorithms can Transformers Learn? A Study in Length Generalization. ICLR 2024 - [c31]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Vaishaal Shankar, Alexander T. Toshev, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. ICML 2024 - [c30]Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind:
Data-free Distillation of Diffusion Models with Bootstrapping. ICML 2024 - [c29]Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista:
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation. ICML 2024 - [c28]Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Joshua M. Susskind:
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. NeurIPS 2024 - [c27]Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind:
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. NeurIPS 2024 - [c26]Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind:
How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. NeurIPS 2024 - 2023
- [c25]Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind:
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors. ICLR 2023 - [c24]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind:
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. ICLR 2023 - [c23]Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista:
Diffusion Probabilistic Fields. ICLR 2023 - [c22]Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M. Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi:
NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion. ICML 2023: 11808-11826 - [c21]Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind:
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. ICML 2023: 40770-40803 - [c20]Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly:
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. NeurIPS 2023 - [c19]Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind:
Transformers learn through gradual rank increase. NeurIPS 2023 - 2022
- [c18]Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind:
Learning Representation from Neural Fisher Kernel with Low-rank Approximation. ICLR 2022 - [c17]Chen Huang, Walter Talbott, Navdeep Jaitly, Joshua M. Susskind:
Efficient Representation Learning via Adaptive Context Pooling. ICML 2022: 9346-9355 - [c16]Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y. Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind:
Position Prediction as an Effective Pretraining Strategy. ICML 2022: 26010-26027 - [c15]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind:
Regularized Training of Nearest Neighbor Language Models. NAACL-HLT (Student Research Workshop) 2022: 25-30 - [c14]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:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. NeurIPS 2022 - [c13]Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan:
Fast and Explicit Neural View Synthesis. WACV 2022: 11-20 - 2021
- [c12]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning To Optimize Black-Box Evaluation Metrics. CVPR 2021: 174-183 - [c11]Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Ángel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind:
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding. ICCV 2021: 10892-10902 - [c10]Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind:
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. ICCV 2021: 14284-14293 - [c9]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. ICML 2021: 11319-11328 - [c8]Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind:
On the generalization of learning-based 3D reconstruction. WACV 2021: 2179-2188 - 2020
- [c7]Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh M. Susskind, Qi Shan:
Equivariant Neural Rendering. ICML 2020: 2761-2770 - [c6]Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan:
Collegial Ensembles. NeurIPS 2020 - 2019
- [c5]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. ICML 2019: 2891-2900 - [c4]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. NeurIPS 2019: 11156-11166 - 2011
- [c3]Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys
:
Modeling the joint density of two images under a variety of transformations. CVPR 2011: 2793-2800 - [c2]Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton:
On deep generative models with applications to recognition. CVPR 2011: 2857-2864 - 2008
- [c1]Vinod Nair, Joshua M. Susskind, Geoffrey E. Hinton:
Analysis-by-Synthesis by Learning to Invert Generative Black Boxes. ICANN (1) 2008: 971-981
Informal and Other Publications
- 2025
- [i64]Samira Abnar, Harshay Shah, Dan Busbridge, Alaaeldin Mohamed Elnouby Ali, Joshua M. Susskind, Vimal Thilak:
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models. CoRR abs/2501.12370 (2025) - [i63]Arwen Bradley, Preetum Nakkiran, David Berthelot, James Thornton, Joshua M. Susskind:
Mechanisms of Projective Composition of Diffusion Models. CoRR abs/2502.04549 (2025) - [i62]Mustafa Shukor, Enrico Fini, Victor Guilherme Turrisi da Costa, Matthieu Cord, Joshua M. Susskind, Alaaeldin El-Nouby:
Scaling Laws for Native Multimodal Models. CoRR abs/2504.07951 (2025) - [i61]Ruixiang Zhang, Shuangfei Zhai, Yizhe Zhang, James Thornton, Zijing Ou, Joshua M. Susskind, Navdeep Jaitly:
Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion. CoRR abs/2504.16431 (2025) - 2024
- [i60]Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin:
Scalable Pre-training of Large Autoregressive Image Models. CoRR abs/2401.08541 (2024) - [i59]Yuhang Zang, Hanlin Goh, Josh M. Susskind, Chen Huang:
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. CoRR abs/2401.15914 (2024) - [i58]Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly:
How Far Are We from Intelligent Visual Deductive Reasoning? CoRR abs/2403.04732 (2024) - [i57]Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu:
Many-to-many Image Generation with Auto-regressive Diffusion Models. CoRR abs/2404.03109 (2024) - [i56]Nick Stracke, Stefan Andreas Baumann, Joshua M. Susskind, Miguel Ángel Bautista, Björn Ommer:
CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. CoRR abs/2405.07913 (2024) - [i55]Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind:
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. CoRR abs/2405.21048 (2024) - [i54]Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Josh M. Susskind, Navdeep Jaitly, Shuangfei Zhai:
Improving GFlowNets for Text-to-Image Diffusion Alignment. CoRR abs/2406.00633 (2024) - [i53]Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind:
How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. CoRR abs/2407.03475 (2024) - [i52]Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Josh M. Susskind, Shuangfei Zhai:
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation. CoRR abs/2410.08159 (2024) - [i51]Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Josh M. Susskind:
Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. CoRR abs/2410.23698 (2024) - [i50]Georgia Gabriela Sampaio, Ruixiang Zhang, Shuangfei Zhai, Jiatao Gu, Josh M. Susskind, Navdeep Jaitly, Yizhe Zhang:
TypeScore: A Text Fidelity Metric for Text-to-Image Generative Models. CoRR abs/2411.02437 (2024) - [i49]Enrico Fini, Mustafa Shukor, Xiujun Li, Philipp Dufter, Michal Klein, David Haldimann, Sai Aitharaju, Victor Guilherme Turrisi da Costa, Louis Béthune, Zhe Gan, Alexander T. Toshev, Marcin Eichner, Moin Nabi, Yinfei Yang, Joshua M. Susskind, Alaaeldin El-Nouby:
Multimodal Autoregressive Pre-training of Large Vision Encoders. CoRR abs/2411.14402 (2024) - [i48]Qihang Zhang, Shuangfei Zhai, Miguel Ángel Bautista, Kevin Miao, Alexander Toshev, Joshua M. Susskind, Jiatao Gu:
World-consistent Video Diffusion with Explicit 3D Modeling. CoRR abs/2412.01821 (2024) - [i47]Yuyang Wang, Anurag Ranjan, Joshua M. Susskind, Miguel Ángel Bautista:
Coordinate In and Value Out: Training Flow Transformers in Ambient Space. CoRR abs/2412.03791 (2024) - [i46]Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Navdeep Jaitly, Joshua M. Susskind:
Normalizing Flows are Capable Generative Models. CoRR abs/2412.06329 (2024) - [i45]Jen-Hao Rick Chang, Yuyang Wang, Miguel Ángel Bautista, Jiatao Gu, Joshua M. Susskind, Oncel Tuzel:
3D Shape Tokenization. CoRR abs/2412.15618 (2024) - 2023
- [i44]Jiatao Gu, Alex Trevithick, Kai-En Lin, Josh M. Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi:
NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion. CoRR abs/2302.10109 (2023) - [i43]Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista:
Diffusion Probabilistic Fields. CoRR abs/2303.00165 (2023) - [i42]Chen Huang, Hanlin Goh, Jiatao Gu, Josh M. Susskind:
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors. CoRR abs/2303.03679 (2023) - [i41]Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind:
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. CoRR abs/2303.06296 (2023) - [i40]Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind:
Learning Controllable 3D Diffusion Models from Single-view Images. CoRR abs/2304.06700 (2023) - [i39]Ahmed A. A. Elhag, Joshua M. Susskind, Miguel Ángel Bautista:
Manifold Diffusion Fields. CoRR abs/2305.15586 (2023) - [i38]Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly:
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. CoRR abs/2306.02531 (2023) - [i37]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Josh M. Susskind:
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping. CoRR abs/2306.05544 (2023) - [i36]Enric Boix-Adserà, Etai Littwin, Emmanuel Abbe, Samy Bengio, Joshua M. Susskind:
Transformers learn through gradual rank increase. CoRR abs/2306.07042 (2023) - [i35]Bogdan Mazoure, Walter Talbott, Miguel Ángel Bautista, R. Devon Hjelm, Alexander Toshev, Joshua M. Susskind:
Value function estimation using conditional diffusion models for control. CoRR abs/2306.07290 (2023) - [i34]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:
Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation. CoRR abs/2309.11669 (2023) - [i33]Stéphane d'Ascoli, Samy Bengio, Josh M. Susskind, Emmanuel Abbe:
Boolformer: Symbolic Regression of Logic Functions with Transformers. CoRR abs/2309.12207 (2023) - [i32]Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Josh M. Susskind, Shuangfei Zhai:
Generative Modeling with Phase Stochastic Bridges. CoRR abs/2310.07805 (2023) - [i31]Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing:
Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today? CoRR abs/2310.08587 (2023) - [i30]Samira Abnar, Omid Saremi, Laurent Dinh, Shantel Wilson, Miguel Ángel Bautista, Chen Huang, Vimal Thilak, Etai Littwin, Jiatao Gu, Josh M. Susskind, Samy Bengio:
Adaptivity and Modularity for Efficient Generalization Over Task Complexity. CoRR abs/2310.08866 (2023) - [i29]Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind:
When can transformers reason with abstract symbols? CoRR abs/2310.09753 (2023) - [i28]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Josh M. Susskind, Navdeep Jaitly:
Matryoshka Diffusion Models. CoRR abs/2310.15111 (2023) - [i27]Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Josh M. Susskind, Samy Bengio, Preetum Nakkiran:
What Algorithms can Transformers Learn? A Study in Length Generalization. CoRR abs/2310.16028 (2023) - [i26]Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin:
Vanishing Gradients in Reinforcement Finetuning of Language Models. CoRR abs/2310.20703 (2023) - [i25]Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista:
Generating Molecular Conformer Fields. CoRR abs/2311.17932 (2023) - [i24]Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin:
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. CoRR abs/2312.04000 (2023) - 2022
- [i23]Martin Bertran Lopez, Walter Talbott, Nitish Srivastava, Joshua M. Susskind:
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation. CoRR abs/2201.12300 (2022) - [i22]Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Josh M. Susskind:
Learning Representation from Neural Fisher Kernel with Low-rank Approximation. CoRR abs/2202.01944 (2022) - [i21]Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind:
The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon. CoRR abs/2206.04817 (2022) - [i20]Chen Huang, Walter Talbott, Navdeep Jaitly, Josh M. Susskind:
Efficient Representation Learning via Adaptive Context Pooling. CoRR abs/2207.01844 (2022) - [i19]Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Yitan Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind:
Position Prediction as an Effective Pretraining Strategy. CoRR abs/2207.07611 (2022) - [i18]Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Josh M. Susskind:
GAUDI: A Neural Architect for Immersive 3D Scene Generation. CoRR abs/2207.13751 (2022) - [i17]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Josh M. Susskind:
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. CoRR abs/2210.04955 (2022) - 2021
- [i16]Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind:
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. CoRR abs/2104.00670 (2021) - [i15]Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind:
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics. CoRR abs/2104.10631 (2021) - [i14]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. CoRR abs/2105.08140 (2021) - [i13]Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh M. Susskind:
An Attention Free Transformer. CoRR abs/2105.14103 (2021) - [i12]Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang:
Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. CoRR abs/2107.00364 (2021) - [i11]Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua M. Susskind:
Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks. CoRR abs/2107.01301 (2021) - [i10]Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan:
Fast and Explicit Neural View Synthesis. CoRR abs/2107.05775 (2021) - [i9]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Josh M. Susskind:
Regularized Training of Nearest Neighbor Language Models. CoRR abs/2109.08249 (2021) - [i8]Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Josh M. Susskind:
Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models. CoRR abs/2112.01163 (2021) - 2020
- [i7]Emilien Dupont, Miguel Ángel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh M. Susskind, Qi Shan:
Equivariant Neural Rendering. CoRR abs/2006.07630 (2020) - [i6]Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan:
Collegial Ensembles. CoRR abs/2006.07678 (2020) - [i5]Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Carlos Guestrin, Josh M. Susskind:
Set Distribution Networks: a Generative Model for Sets of Images. CoRR abs/2006.10705 (2020) - [i4]Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind:
On the generalization of learning-based 3D reconstruction. CoRR abs/2006.15427 (2020) - 2019
- [i3]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. CoRR abs/1905.05895 (2019) - [i2]Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind:
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking. CoRR abs/1910.12770 (2019) - [i1]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. CoRR abs/1910.13101 (2019)
Coauthor Index
[j3] [j2] [c43] [c42] [c38] [c36] [c31] [c30] [c27] [c24] [c21] [c20] [c18] [c16] [c15] [c14] [c12] [c9] [c8] [c6] [c5] [c4] [i61] [i60] [i58] [i57] [i55] [i54] [i52] [i50] [i48] [i46] [i41] [i40] [i38] [i37] [i32] [i28] [i22] [i21] [i19] [i18] [i17] [i15] [i14] [i13] [i12] [i9] [i8] [i6] [i5] [i4] [i3] [i2] [i1]
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