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Tutorial
Mon 8:00 Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
Ahmed M. Alaa, Mihaela van der Schaar
Tutorial
Mon 8:00 Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
Ahmed M. Alaa, Mihaela van der Schaar
Spotlight
Tue 5:35 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Oral
Tue 6:00 Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison
Spotlight
Tue 6:20 Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
Spotlight
Tue 6:25 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Spotlight
Tue 6:30 Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Spotlight
Tue 6:35 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Spotlight
Tue 6:40 Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
Spotlight
Tue 6:40 Self Normalizing Flows
T. Anderson Keller, Jorn Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
Spotlight
Tue 6:45 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks
Xuhui Fan, Bin Li, Yaqiong Li, Scott SIsson
Oral
Tue 7:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Spotlight
Tue 7:20 Riemannian Convex Potential Maps
samuel cohen, Brandon Amos, Yaron Lipman
Spotlight
Tue 7:25 Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Spotlight
Tue 7:30 PixelTransformer: Sample Conditioned Signal Generation
Shubham Tulsiani, Abhinav Gupta
Spotlight
Tue 7:35 Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Spotlight
Tue 7:35 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
Spotlight
Tue 7:40 Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or
Spotlight
Tue 7:45 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 PixelTransformer: Sample Conditioned Signal Generation
Shubham Tulsiani, Abhinav Gupta
Poster
Tue 9:00 Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or
Poster
Tue 9:00 Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
Poster
Tue 9:00 Self Normalizing Flows
T. Anderson Keller, Jorn Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
Poster
Tue 9:00 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Poster
Tue 9:00 Riemannian Convex Potential Maps
samuel cohen, Brandon Amos, Yaron Lipman
Poster
Tue 9:00 NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo J. Rezende
Poster
Tue 9:00 Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Poster
Tue 9:00 Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Poster
Tue 9:00 Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison
Poster
Tue 9:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Poster
Tue 9:00 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks
Xuhui Fan, Bin Li, Yaqiong Li, Scott SIsson
Poster
Tue 9:00 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Poster
Tue 9:00 Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Poster
Tue 9:00 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
Poster
Tue 9:00 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Poster
Tue 9:00 Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
Oral
Tue 17:00 NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo J. Rezende
Spotlight
Tue 17:20 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Spotlight
Tue 17:25 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Spotlight
Tue 17:25 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Spotlight
Tue 17:25 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Spotlight
Tue 17:30 Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Josh Tenenbaum, Igor Mordatch
Spotlight
Tue 17:35 Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
Spotlight
Tue 17:40 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Spotlight
Tue 17:45 Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath
Oral
Tue 18:00 Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia
Spotlight
Tue 18:20 An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi
Spotlight
Tue 18:25 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Spotlight
Tue 18:30 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Spotlight
Tue 18:35 Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann
Spotlight
Tue 18:40 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Spotlight
Tue 18:45 Zero-Shot Text-to-Image Generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Spotlight
Tue 19:40 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Poster
Tue 21:00 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Poster
Tue 21:00 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Poster
Tue 21:00 An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi
Poster
Tue 21:00 Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
Poster
Tue 21:00 Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath
Poster
Tue 21:00 Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Josh Tenenbaum, Igor Mordatch
Poster
Tue 21:00 Zero-Shot Text-to-Image Generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Poster
Tue 21:00 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Poster
Tue 21:00 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Poster
Tue 21:00 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Poster
Tue 21:00 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Poster
Tue 21:00 Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann
Poster
Tue 21:00 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Poster
Tue 21:00 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Poster
Tue 21:00 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Poster
Tue 21:00 Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia
Spotlight
Wed 5:30 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Spotlight
Wed 5:30 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Spotlight
Wed 5:35 ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables
Alek Dimitriev, Mingyuan Zhou
Spotlight
Wed 5:45 Nonparametric Hamiltonian Monte Carlo
Carol Mak, Fabian Zaiser, Luke Ong
Spotlight
Wed 5:45 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 6:25 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Spotlight
Wed 6:40 Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho (Johann) Won
Spotlight
Wed 7:25 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Spotlight
Wed 7:40 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Spotlight
Wed 7:45 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Poster
Wed 9:00 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Poster
Wed 9:00 ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables
Alek Dimitriev, Mingyuan Zhou
Poster
Wed 9:00 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Poster
Wed 9:00 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Poster
Wed 9:00 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Poster
Wed 9:00 Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho (Johann) Won
Poster
Wed 9:00 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Poster
Wed 9:00 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Poster
Wed 9:00 Nonparametric Hamiltonian Monte Carlo
Carol Mak, Fabian Zaiser, Luke Ong
Poster
Wed 9:00 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 17:40 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Oral
Wed 19:00 Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
Spotlight
Wed 19:35 Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
yue cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Poster
Wed 21:00 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Poster
Wed 21:00 Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
Poster
Wed 21:00 Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
yue cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Spotlight
Thu 5:40 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Spotlight
Thu 5:45 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Spotlight
Thu 7:20 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Spotlight
Thu 7:20 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Spotlight
Thu 7:30 GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic
Spotlight
Thu 7:35 Adversarial Purification with Score-based Generative Models
Jongmin Yoon, Sung Ju Hwang, Juho Lee
Poster
Thu 9:00 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Poster
Thu 9:00 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Poster
Thu 9:00 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Poster
Thu 9:00 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Poster
Thu 9:00 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Poster
Thu 9:00 Adversarial Purification with Score-based Generative Models
Jongmin Yoon, Sung Ju Hwang, Juho Lee
Poster
Thu 9:00 GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic
Oral
Thu 17:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Spotlight
Thu 17:30 Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
José Lezama, Wei Chen, Qiang Qiu
Spotlight
Thu 17:30 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Spotlight
Thu 17:40 Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora
Oral
Thu 18:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Spotlight
Thu 18:20 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Spotlight
Thu 19:25 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Spotlight
Thu 19:30 Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Spotlight
Thu 19:40 Streaming and Distributed Algorithms for Robust Column Subset Selection
Shuli Jiang, Dongyu Li, Irene Mengze Li, Arvind Mahankali, David Woodruff
Spotlight
Thu 20:45 A Language for Counterfactual Generative Models
zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama
Spotlight
Thu 20:45 Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, MANIK KUCHROO, Ronald Coifman, Guy Wolf, Smita Krishnaswamy
Poster
Thu 21:00 Streaming and Distributed Algorithms for Robust Column Subset Selection
Shuli Jiang, Dongyu Li, Irene Mengze Li, Arvind Mahankali, David Woodruff
Poster
Thu 21:00 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Poster
Thu 21:00 Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora
Poster
Thu 21:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Poster
Thu 21:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Poster
Thu 21:00 A Language for Counterfactual Generative Models
zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama
Poster
Thu 21:00 Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, MANIK KUCHROO, Ronald Coifman, Guy Wolf, Smita Krishnaswamy
Poster
Thu 21:00 Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Poster
Thu 21:00 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Poster
Thu 21:00 Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
José Lezama, Wei Chen, Qiang Qiu
Poster
Thu 21:00 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Workshop
Fri 2:28 INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models
Chin-Wei Huang, David Krueger, Rianne Van den Berg, George Papamakarios, Ricky T. Q. Chen, Danilo J. Rezende
Workshop
Fri 9:00 Invited Talk 7 (Aditya Ramesh): Scaling up generative models
Aditya Ramesh
Workshop
Sat 11:45 Morning Poster Session: Changepoint Detection using Self Supervised Variational AutoEncoders
Sourav Chatterjee
Workshop
Sat 11:55 Spotlight Set 2-2 | Viral Evolution and Antibody Escape Mutations using Deep Generative Models
Workshop CompBio, Nicole Thadani
Workshop
Representation Learning in Continuous-Time Score-Based Generative Models
Korbinian Abstreiter
Workshop
A Variational Perspective on Diffusion-Based Generative Models and Score Matching
Chin-Wei Huang
Workshop
Non-Robust Feature Mapping in Deep Reinforcement Learning
Ezgi Korkmaz
Workshop
Demystifying Adversarial Training via A Unified Probabilistic Framework
Zhouchen Lin, Yisen Wang, Jiansheng Yang, Yifei Wang
Workshop
Differentially Private Active Learning with Latent Space Optimization
Samson Cheung, Xiaoqing Zhu, Herb Wildfeuer, Chongruo Wu, Wai-tian Tan
Workshop
Measuring Fairness in Generative Models
Chris Teo, Ngai-Man Cheung
Workshop
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
Terrance Liu, Giuseppe Vietri, Steven Wu
Workshop
Entropic Causal Inference: Identifiability for Trees and Complete Graphs
Spencer Compton, Murat Kocaoglu, Kristjan Greenewald, Dmitriy Katz
Workshop
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
Terrance Liu, Giuseppe Vietri, Steven Wu
Workshop
A comparative study of stochastic and deep generative models for multisite precipitation synthesis
Jorge Luis Guevara Diaz
Workshop
MultImp: Multiomics Generative Models for Data Imputation
Yining Jiao
Workshop
Viral Evolution and Antibody Escape Mutations using Deep Generative Models
Nicole Thadani
Workshop
Reconstructing unobserved cellular states from paired single-cell lineage tracing and transcriptomics data
Khalil Ouardini
Workshop
Exploring the latent space of deep generative models: Applications to G-protein coupled receptors
Lood van Niekerk
Workshop
Multi-target optimization for drug discovery using generative models
Anirudh jain
Workshop
De novo drug design using reinforcement learning with graph-based deep generative models
Sara Romeo Atance, Ola Engkvist, Simon Olsson, Rocío Mercado
Workshop
What Can I Do Here? Learning New Skills by Imagining Visual Affordances
Khazatsky Alexander, Ashvin Nair
Workshop
Machine Teaching with Generative Models for Human Learning
Michael Doron, Hussein Mozannar, David Sontag, Juan Caicedo
Workshop
PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno
Workshop
Improving Image-Based Characterization of Porous Media with Deep Generative Models
Timothy Anderson