Title
Offline Model-Based Optimization by Learning to Rank Rong-Xi Tan Ke Xue Shen-Huan Lyu Haopu Shang Yao Wang Yaoyuan Wang Sheng Fu Chao Qian OffRL 94 3 0 15 Oct 2024
Sora as an AGI World Model? A Complete Survey on Text-to-Video Generation Joseph Cho Fachrina Dewi Puspitasari Sheng Zheng Jingyao Zheng Lik-Hang Lee Tae-Ho Kim Choong Seon Hong Chaoning Zhang EGVM VGen 64 42 0 08 Mar 2024
ExPT: Synthetic Pretraining for Few-Shot Experimental Design Tung Nguyen Sudhanshu Agrawal Aditya Grover 85 17 0 30 Oct 2023
Learning Concept-Based Causal Transition and Symbolic Reasoning for Visual Planning Yilue Qian Peiyu Yu Ying Nian Wu Yao Su Wei Wang Lifeng Fan LRM 69 4 0 05 Oct 2023
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting Deqian Kong Bo Pang Tian Han Ying Nian Wu DiffM 63 7 0 09 Jun 2023
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent Jiaxin Shi Lester W. Mackey 50 19 0 17 Nov 2022
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model Zhisheng Xiao Tian Han 74 15 0 19 Sep 2022
Generative Pretraining for Black-Box Optimization S. Krishnamoorthy Satvik Mashkaria Aditya Grover OffRL AI4CE 90 31 0 22 Jun 2022
Latent Diffusion Energy-Based Model for Interpretable Text Modeling Peiyu Yu Sirui Xie Xiaojian Ma Baoxiong Jia Bo Pang Ruigi Gao Yixin Zhu Song-Chun Zhu Ying Nian Wu DiffM 62 82 0 13 Jun 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 262 30,123 0 01 Mar 2022
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization Brandon Trabucco Xinyang Geng Aviral Kumar Sergey Levine OffRL 71 100 0 17 Feb 2022
Unsupervised Foreground Extraction via Deep Region Competition Peiyu Yu Sirui Xie Xiaojian Ma Yixin Zhu Ying Nian Wu Song-Chun Zhu OCL 53 42 0 29 Oct 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 76 14 0 06 Oct 2021
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation Justin Fu Sergey Levine OffRL 98 49 0 16 Feb 2021
Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao Yang Song Ben Poole Ying Nian Wu Diederik P. Kingma DiffM 54 128 0 15 Dec 2020
A Contrastive Learning Approach for Training Variational Autoencoder Priors J. Aneja Alex Schwing Jan Kautz Arash Vahdat DRL 59 83 0 06 Oct 2020
Chip Placement with Deep Reinforcement Learning Azalia Mirhoseini Anna Goldie M. Yazgan J. Jiang Ebrahim M. Songhori ... Quoc V. Le James Laudon Richard Ho Roger Carpenter J. Dean OffRL 53 217 0 22 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 356 18,739 0 13 Feb 2020
Model Inversion Networks for Model-Based Optimization Aviral Kumar Sergey Levine OffRL 77 100 0 31 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 78 542 0 06 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 449 42,393 0 03 Dec 2019
Knowing The What But Not The Where in Bayesian Optimization Vu Nguyen Michael A. Osborne 45 38 0 07 May 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 79 212 0 22 Apr 2019
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models Erik Nijkamp Mitch Hill Tian Han Song-Chun Zhu Ying Nian Wu 52 154 0 29 Mar 2019
Conditioning by adaptive sampling for robust design David H. Brookes Hahnbeom Park Jennifer Listgarten 52 199 0 29 Jan 2019
Attentive Neural Processes Hyunjik Kim A. Mnih Jonathan Richard Schwarz M. Garnelo S. M. Ali Eslami Dan Rosenbaum Oriol Vinyals Yee Whye Teh 88 441 0 17 Jan 2019
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 287 3,128 0 09 Jul 2018
Conditional Neural Processes M. Garnelo Dan Rosenbaum Chris J. Maddison Tiago Ramalho D. Saxton Murray Shanahan Yee Whye Teh Danilo Jimenez Rezende S. M. Ali Eslami UQCV BDL 88 701 0 04 Jul 2018
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups Paul Rolland Jonathan Scarlett Ilija Bogunovic Volkan Cevher 61 115 0 20 Feb 2018
VAE with a VampPrior Jakub M. Tomczak Max Welling GAN BDL 66 633 0 19 May 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 153 2,927 0 07 Oct 2016
Neural Photo Editing with Introspective Adversarial Networks Andrew Brock Theodore Lim J. Ritchie Nick Weston GAN 72 458 0 22 Sep 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 65 1,092 0 16 Aug 2016
Safe Controller Optimization for Quadrotors with Gaussian Processes Felix Berkenkamp Angela P. Schoellig Andreas Krause 64 301 0 03 Sep 2015
Active Learning of Linear Embeddings for Gaussian Processes Roman Garnett Michael A. Osborne Philipp Hennig GP 91 92 0 24 Oct 2013
A Fast and Simple Algorithm for Training Neural Probabilistic Language Models A. Mnih Yee Whye Teh 161 578 0 27 Jun 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 351 7,934 0 13 Jun 2012