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Artificial Intelligence and Machine Learning

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2022

DefGraspSim: Physics-Based Simulation of Grasp Outcomes on 3D Deformable Objects

Isabella Huang, Yashraj Narang, Clemens Eppner, Balakumar Sundaralingam, Miles Macklin, Ruzena Bajcsy, Tucker Hermans, Dieter Fox

DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators

Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna

Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks

Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Mark Kilgard, Anima Anandkumar, Brucek Khailany, Vivek Singh, Haoxing (Mark) Ren

Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

Jingkai Chen, Jiaoyang Li, Yijiang Huang, Caelan Garrett, Dawei Sun, Chuchu Fan, Andreas Hofmann, Caitlin Mueller, Sven Koenig, Brian Williams

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Tim Dockhorn, Arash Vahdat, Karsten Kreis

ICLR

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Zhisheng Xiao, Karsten Kreis, Arash Vahdat

ICLR

Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators

Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar

Reinforcement Learning for Datacenter Congestion Control

Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mendelbaum, Doron Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor

Machine Learning and Algorithms: Let Us Team Up for EDA

Haoxing (Mark) Ren, Brucek Khailany, Matt Fojtik, Yanqing Zhang