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2020 – today
- 2024
[c30]Siddhant Jain, Daniel Watson, Eric Tabellion, Aleksander Holynski, Ben Poole, Janne Kontkanen:
Video Interpolation with Diffusion Models. CVPR 2024: 7341-7351- [c29]Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski:
ReconFusion: 3D Reconstruction with Diffusion Priors. CVPR 2024: 21551-21561 - [c28]Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A. Efros, Aleksander Holynski:
Disentangled 3D Scene Generation with Layout Learning. ICML 2024 - [i44]Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A. Efros, Aleksander Holynski:
Disentangled 3D Scene Generation with Layout Learning. CoRR abs/2402.16936 (2024) - [i43]Siddhant Jain, Daniel Watson, Eric Tabellion, Aleksander Holynski, Ben Poole, Janne Kontkanen:
Video Interpolation with Diffusion Models. CoRR abs/2404.01203 (2024) - [i42]Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, Ben Poole:
CAT3D: Create Anything in 3D with Multi-View Diffusion Models. CoRR abs/2405.10314 (2024) - [i41]Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao:
EM Distillation for One-step Diffusion Models. CoRR abs/2405.16852 (2024) - 2023
- [c27]Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan T. Barron, Yuanzhen Li, Varun Jampani:
DreamBooth3D: Subject-Driven Text-to-3D Generation. ICCV 2023: 2349-2359 - [c26]Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall:
DreamFusion: Text-to-3D using 2D Diffusion. ICLR 2023 - [c25]Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski:
Diffusion Self-Guidance for Controllable Image Generation. NeurIPS 2023 - [i40]Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan T. Barron, Yuanzhen Li, Varun Jampani:
DreamBooth3D: Subject-Driven Text-to-3D Generation. CoRR abs/2303.13508 (2023) - [i39]Guandao Yang, Abhijit Kundu, Leonidas J. Guibas, Jonathan T. Barron, Ben Poole:
Learning a Diffusion Prior for NeRFs. CoRR abs/2304.14473 (2023) - [i38]Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski:
Diffusion Self-Guidance for Controllable Image Generation. CoRR abs/2306.00986 (2023) - [i37]Alexander A. Alemi, Ben Poole:
Variational Prediction. CoRR abs/2307.07568 (2023) - [i36]Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski:
ReconFusion: 3D Reconstruction with Diffusion Priors. CoRR abs/2312.02981 (2023) - [i35]Kira Prabhu, Jane Wu, Lynn Tsai, Peter Hedman
, Dan B. Goldman, Ben Poole, Michael Broxton:
Inpaint3D: 3D Scene Content Generation using 2D Inpainting Diffusion. CoRR abs/2312.03869 (2023) - 2022
- [c24]Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole:
Zero-Shot Text-Guided Object Generation with Dream Fields. CVPR 2022: 857-866 - [c23]Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans:
Autoregressive Diffusion Models. ICLR 2022 - [i34]Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall:
DreamFusion: Text-to-3D using 2D Diffusion. CoRR abs/2209.14988 (2022) - [i33]Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans:
Imagen Video: High Definition Video Generation with Diffusion Models. CoRR abs/2210.02303 (2022) - [i32]Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein:
VeLO: Training Versatile Learned Optimizers by Scaling Up. CoRR abs/2211.09760 (2022) - 2021
- [c22]Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole:
Score-Based Generative Modeling through Stochastic Differential Equations. ICLR 2021 - [c21]Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma:
Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR 2021 - [c20]Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho:
On Density Estimation with Diffusion Models. NeurIPS 2021: 21696-21707 - [i31]Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho:
Variational Diffusion Models. CoRR abs/2107.00630 (2021) - [i30]Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans:
Autoregressive Diffusion Models. CoRR abs/2110.02037 (2021) - [i29]Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole:
Zero-Shot Text-Guided Object Generation with Dream Fields. CoRR abs/2112.01455 (2021) - 2020
- [c19]Abhishek Kumar, Ben Poole, Kevin Murphy:
Regularized Autoencoders via Relaxed Injective Probability Flow. AISTATS 2020: 4292-4301 - [c18]Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole:
Weakly Supervised Disentanglement with Guarantees. ICLR 2020 - [c17]Abhishek Kumar, Ben Poole:
On Implicit Regularization in β-VAEs. ICML 2020: 5480-5490 - [c16]Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen:
Weakly-Supervised Disentanglement Without Compromises. ICML 2020: 6348-6359 - [c15]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What Makes for Good Views for Contrastive Learning? NeurIPS 2020 - [i28]Abhishek Kumar, Ben Poole:
On Implicit Regularization in β-VAEs. CoRR abs/2002.00041 (2020) - [i27]Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen:
Weakly-Supervised Disentanglement Without Compromises. CoRR abs/2002.02886 (2020) - [i26]Abhishek Kumar, Ben Poole, Kevin Murphy:
Regularized Autoencoders via Relaxed Injective Probability Flow. CoRR abs/2002.08927 (2020) - [i25]Luke Metz, Niru Maheswaranathan, Ruoxi Sun, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein:
Using a thousand optimization tasks to learn hyperparameter search strategies. CoRR abs/2002.11887 (2020) - [i24]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What makes for good views for contrastive learning. CoRR abs/2005.10243 (2020) - [i23]Luke Metz, Niru Maheswaranathan, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein:
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves. CoRR abs/2009.11243 (2020) - [i22]Matt Shannon, Ben Poole, Soroosh Mariooryad, Tom Bagby, Eric Battenberg, David Kao, Daisy Stanton, R. J. Skerry-Ryan:
Non-saturating GAN training as divergence minimization. CoRR abs/2010.08029 (2020) - [i21]Alexander A. Alemi, Warren R. Morningstar, Ben Poole, Ian Fischer, Joshua V. Dillon:
VIB is Half Bayes. CoRR abs/2011.08711 (2020) - [i20]Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole:
Score-Based Generative Modeling through Stochastic Differential Equations. CoRR abs/2011.13456 (2020) - [i19]Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma:
Learning Energy-Based Models by Diffusion Recovery Likelihood. CoRR abs/2012.08125 (2020)
2010 – 2019
- 2019
- [c14]Ali Razavi, Aäron van den Oord, Ben Poole, Oriol Vinyals:
Preventing Posterior Collapse with delta-VAEs. ICLR (Poster) 2019 - [c13]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. DGS@ICLR 2019 - [c12]Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker:
On Variational Bounds of Mutual Information. ICML 2019: 5171-5180 - [c11]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. NeurIPS 2019: 14692-14701 - [i18]Ali Razavi, Aäron van den Oord, Ben Poole, Oriol Vinyals:
Preventing Posterior Collapse with delta-VAEs. CoRR abs/1901.03416 (2019) - [i17]Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker:
On Variational Bounds of Mutual Information. CoRR abs/1905.06922 (2019) - [i16]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. CoRR abs/1905.10347 (2019) - [i15]Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, Ekin D. Cubuk:
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation. CoRR abs/1906.02611 (2019) - [i14]Zhe Dong, Deniz Oktay, Ben Poole, Alexander A. Alemi:
On Predictive Information Sub-optimality of RNNs. CoRR abs/1910.09578 (2019) - [i13]Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole:
Weakly Supervised Disentanglement with Guarantees. CoRR abs/1910.09772 (2019) - 2018
- [c10]Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy:
Fixing a Broken ELBO. ICML 2018: 159-168 - 2017
- [c9]Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville:
Adversarially Learned Inference. ICLR (Poster) 2017 - [c8]Eric Jang, Shixiang Gu, Ben Poole:
Categorical Reparameterization with Gumbel-Softmax. ICLR (Poster) 2017 - [c7]Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein:
Unrolled Generative Adversarial Networks. ICLR (Poster) 2017 - [c6]Ben Poole, Friedemann Zenke, Surya Ganguli:
Intelligent synapses for multi-task and transfer learning. ICLR (Workshop) 2017 - [c5]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
On the Expressive Power of Deep Neural Networks. ICML 2017: 2847-2854 - [c4]Friedemann Zenke, Ben Poole, Surya Ganguli:
Continual Learning Through Synaptic Intelligence. ICML 2017: 3987-3995 - [i12]Friedemann Zenke, Ben Poole, Surya Ganguli:
Improved multitask learning through synaptic intelligence. CoRR abs/1703.04200 (2017) - [i11]Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy:
An Information-Theoretic Analysis of Deep Latent-Variable Models. CoRR abs/1711.00464 (2017) - 2016
- [c3]Jonathan T. Barron, Ben Poole:
The Fast Bilateral Solver. ECCV (3) 2016: 617-632 - [c2]Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli:
Exponential expressivity in deep neural networks through transient chaos. NIPS 2016: 3360-3368 - [i10]Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville:
Adversarially Learned Inference. CoRR abs/1606.00704 (2016) - [i9]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
On the expressive power of deep neural networks. CoRR abs/1606.05336 (2016) - [i8]Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli:
Exponential expressivity in deep neural networks through transient chaos. CoRR abs/1606.05340 (2016) - [i7]Eric Jang, Shixiang Gu, Ben Poole:
Categorical Reparameterization with Gumbel-Softmax. CoRR abs/1611.01144 (2016) - [i6]Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein:
Unrolled Generative Adversarial Networks. CoRR abs/1611.02163 (2016) - [i5]Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein:
Survey of Expressivity in Deep Neural Networks. CoRR abs/1611.08083 (2016) - [i4]Ben Poole, Alexander A. Alemi, Jascha Sohl-Dickstein, Anelia Angelova:
Improved generator objectives for GANs. CoRR abs/1612.02780 (2016) - 2015
- [i3]Jonathan T. Barron, Ben Poole:
The Fast Bilateral Solver. CoRR abs/1511.03296 (2015) - 2014
- [c1]Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli:
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods. ICML 2014: 604-612 - [i2]Ben Poole, Jascha Sohl-Dickstein, Surya Ganguli:
Analyzing noise in autoencoders and deep networks. CoRR abs/1406.1831 (2014) - 2013
- [i1]Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli:
An adaptive low dimensional quasi-Newton sum of functions optimizer. CoRR abs/1311.2115 (2013) - 2011
- [j1]John R. Anderson, Daniel Bothell, Jon M. Fincham, Abraham R. Anderson, Ben Poole, Yulin Qin:
Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis. J. Cogn. Neurosci. 23(12): 3983-3997 (2011)
Coauthor Index
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last updated on 2024-10-07 02:24 CEST by the dblp team
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