Publications | Research

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Artificial Intelligence and Machine Learning

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2026

GalaxyDiT: Efficient Video Generation with Guidance Alignment and Adaptive Proxy in Diffusion Transformers

Zoey Song, Steve Dai, Ben Keller, Brucek Khailany

ScheduleStream: Temporal Planning with Samplers for GPU-Accelerated Multi-Arm Task and Motion Planning & Scheduling

Caelan Garrett, Fabio Ramos

Test-Time Alignment for Large Language Models via Textual Model Predictive Control

Kuang-Da Wang, Teng-Ruei Chen, Yu Heng Hung, Guo-Xun Ko, Shuoyang Ding, Frank Wang, Huck Yang, Wen-Chih Peng, Ping-Chun Hsieh

ICLR

3D-GENERALIST: Vision-Language-Action Models for Crafting 3D Worlds

Fan-Yun Sun, Shengguang Wu, Christian Jacobsen, Thomas Yim, Haoming Zou, Alex Zook, Shangru Li, Yu-Hsin Chou, Ethem Can, Xunlei Wu, Clemens Eppner, Valts Blukis, Jonathan Tremblay, Jiajun Wu, Stan Birchfield, Nick Haber

SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding

Talor Abramovich, Maor Ashkenazi, Carl Putterman, Benjamin Chislett, Tiyasa Mitra, Bita Darvish Rouhani, Ran Zilberstein, Yonatan Geifman

Alpha-Vision: A Real-Time Always-on Vision Processor with 787µs Face Detection Latency in <5mW

Ben Keller, Rangharajan Venkatesan, Steve Dai, Jason Clemons, Matt Fojtik, Muya Chang, Thierry Tambe, Nathaniel Pinckney, Stephen Tell, Qijing Jenny Huang, Shalini De Mello, Brucek Khailany

Learning Accurate Storm-Scale Evolution from Observations

Jaideep Pathak, Mohammad Shoaib Abbas, Peter Harrington, Zeyuan Hu, Noah Brenowitz, Suman Ravuri, Alberto Carpentieri, Jussi Leinonen, Corey Adams, Oliver Hennigh, Nicholas Geneva, Dale Durran, Mike Pritchard

HealDA: Highlighting the importance of initial errors in end-to-end AI weather forecasts

Aayush Gupta, Akshay Subramaniam, Michael S. Pritchard, Karthik Kashinath, Sergey Frolov, Kelsey Lieberman, Christopher Miller, Nicholas Silverman, Noah D. Brenowitz

Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting

Jean Kossaifi, Nikola Kovachki, Morteza Mardani, Daniel Leibovici, Suman Ravuri, Ira Shokar, Edoardo Calvello, Mohammad Shoaib Abbas, Peter Harrington, Ashay Subramaniam, Noah Brenowitz, Boris Bonev, Wonmin Byeon, Karsten Kreis, Dale Durran, Arash Vahdat, Mike Pritchard, Jan Kautz

2017

Parallel Complexity of Forward and Backward Propagation

Maxim Naumov

Integral Equations and Machine Learning

Alex Keller, Ken Dahm

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks

Aditya Devarakonda, Maxim Naumov, Michael Garland

Unsupervised Image-to-Image Translation Networks

Ming-Yu Liu, Thomas Breuel, Jan Kautz

Learning Affinity via Spatial Propagation Networks

Sifei Liu, Shalini De Mello, Jinwei Gu, Guangyu Zhong, Ming-Hsuan Yang, Jan Kautz

Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications

Guanpeng Li, Siva Hari, Michael B. Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel Emer, Steve Keckler

Parallel Jaccard and Related Graph Clustering Techniques

Alexandre Fender, Nahid Emad, Serge Petiton, Joe Eaton, Maxim Naumov

Learning to Super-Resolve Blurry Face and Text Images

Xiangyu Xu, Deqing Sun, Jinshan Pan, Yujin Zhang, Hanspeter Pfister, Ming-Hsuan Yang

A Lightweight Approach for On-the-Fly Reflectance Estimation

Kihwan Kim, Jinwei Gu, Stephen Tyree, Pavlo Molchanov, Matthias Nießner, Jan Kautz

Group online adaptive learning

Alon Zweig, Gal Chechik

Feedforward and Recurrent Neural Networks Backward Propagation and Hessian in Matrix Form

Maxim Naumov

Tactics of Adversarial Attack on Deep Reinforcement Learning Agents

Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao , Meng-Li Shi, Ming-Yu Liu, Min Sun

Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion

Tero Karras, Timo Aila, Samuli Laine, Antti Herva, Jaakko Lehtinen

Parallel Modularity Clustering

Alexandre Fender, Nahid Emad, Serge Petiton, Maxim Naumov

SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks

Angshuman Parashar, Minsoo Rhu, Anurag Mukkara, Antonio Puglielli, Rangharajan Venkatesan, Brucek Khailany, Joel Emer, Steve Keckler, William Dally

Pruning Convolutional Neural Networks for Resource Efficient Inference

Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, Jan Kautz

Context-aware Captions from Context-agnostic Supervision

Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik

Learning From Noisy Large-Scale Datasets With Minimal Supervision

Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge Belongie

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz, Mohammad Babaeizadeh

Loss Functions for Image Restoration with Neural Networks

Hang Zhao, Orazio Gallo, Iuri Frosio, Jan Kautz