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Joshua M. Susskind
Josh M. Susskind
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- affiliation: Apple
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2020 – today
- 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) - [c39]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 - [c38]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 - [c37]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 - [c36]Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind:
When can transformers reason with abstract symbols? ICLR 2024 - [c35]Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai:
Generative Modeling with Phase Stochastic Bridge. ICLR 2024 - [c34]Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista:
Manifold Diffusion Fields. ICLR 2024 - [c33]Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly:
Matryoshka Diffusion Models. ICLR 2024 - [c32]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 - [c31]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 - [c30]Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang:
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. ICLR 2024 - [c29]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 - [c28]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 - [c27]Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind:
Data-free Distillation of Diffusion Models with Bootstrapping. ICML 2024 - [c26]Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista:
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation. ICML 2024 - [i52]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) - [i51]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) - [i50]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) - [i49]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) - [i48]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) - [i47]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) - [i46]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) - [i45]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) - 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 - [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
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
- [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 - [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
- [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 - [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
- [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 - [i7]Emilien Dupont, Miguel Ángel Bautista, Alex Colburn
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)
2010 – 2019
- 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 - [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) - 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) - 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
2000 – 2009
- 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
Coauthor Index
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