Publications

Our publications provide insight into some of our leading-edge research.

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2024

Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models
Yuchen Hu, Chen Chen, Huck Yang, Chengwei Qin, Pin-Yu Chen, Eng Siong Chng, Chao Zhang
Diffusion-Reward Adversarial Imitation Learning
Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Frank Wang, Min-Hung Chen, Shao-Hua Sun
Fast Encoder-Based 3D from Casual Videos via Point Track Processing
Yoni Kasten, Wuyue Lu, Haggai Maron

2023

Point-Cloud Completion with Pretrained Text-to-image Diffusion Models
Yoni Kasten, Ohad Rahamim, Gal Chechik
Convolutional State Space Models for Long-Range Spatiotemporal Modeling
Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon
Generalizable One-shot 3D Neural Head Avatar
Xueting Li, Shalini De Mello, Sifei Liu, Koki Nagano, Umar Iqbal, Jan Kautz
SceneScape: Text-Driven Consistent Scene Generation
Rafail Fridman, Amit Abecasis, Yoni Kasten, Tali Dekel
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
Chen Chen, YuChen Hu, Huck Yang, Sabato Marco Siniscalchi, Pin-Yu Chen, Ensiong Chng
Syntactic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik
Oral presentation
Norm-guided latent space exploration for text-to-image generation
Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik
Train Hard, Fight Easy: Robust Meta Reinforcement Learning
Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom

2022

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Jiaqi Gu, Ben Keller, Jean Kossaifi, Anima Anandkumar, Brucek Khailany, David Z. Pan
Spotlight Paper
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
Mingjie Liu, Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Selim Dogru, Anima Anandkumar, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS Outstanding Paper
LION: Latent Point Diffusion Models for 3D Shape Generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
Paraphrasing Is All You Need for Novel Object Captioning
Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Frank Wang
Embodied Scene-aware Human Pose Estimation
Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion
Sheng-Yu Huang, Hao-Yu Hsu, Yu-Chiang Frank Wang
GENIE: Higher-Order Denoising Diffusion Solvers
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising
Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg

2021

ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler
Alias-Free Generative Adversarial Networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila
EditGAN: High-Precision Semantic Image Editing
Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler
Controllable and Compositional Generation with Latent-Space Energy-Based Models
Weili Nie, Arash Vahdat, Anima Anandkumar
Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence
Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis
Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik

2020

Variational Amodal Object Completion
Huan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler

2019

Instant Quantization of neural networks using Monte Carlo Methods
Gonçalo Mordido, Matthijs Van keirsbilck, Alex Keller