Publications

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

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  • 153 results found

2023

GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
Chenhongyi Yang, Jiarui Xu, Shalini De Mello, Elliot J. Crowley, Xiaolong Wang
Notable top 25%
Oral
Robust and Controllable Object-Centric Learning through Energy-based Models
Ruixiang Zhang, Gerry Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull
A 9.7fJ/Conv.-Step Capacitive Sensor Readout Circuit with Incremental Zoomed Time Domain Quantization
Zilong Shen, Xiyuan Tang, Zhongyi Wu, Haoyang Luo, Zongnan Wang, Mingjie Liu, Xing Zhang, Yuan Wang
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
Hainan Xu, Fei Jia, Somshubra Majumdar, He Huang, Shinji Watanabe, Boris Ginsburg
Towards a scalable discrete quantum generative adversarial neural network
Smit Chaudhary, Patrick Huembeli, Ian MacCormack, Taylor Patti, Jean Kossaifi, Alexey Galda
A 0.297-pJ/Bit 50.4-Gb/s/Wire Inverter-Based Short-Reach Simultaneous Bi-Directional Transceiver for Die-to-Die Interface in 5-nm CMOS
Yoshinori Nishi, John W. Poulton, Walker Turner, Xi Chen, Sanquan Song, Brian Zimmer, Stephen Tell, Nikola Nedovic, John Wilson, William Dally, Tom Gray
Reinforcement Learning Guided Detailed Routing for Custom Circuits
Hao Chen, Kai-Chieh Hsu, Walker Turner, Po-Hsuan Wei, Keren Zhu, David Z. Pan, Haoxing (Mark) Ren
DREAM-GAN: Advancing DREAMPlace towards Commercial-Quality using Generative Adversarial Learning
Yi-Chen Lu, Haoxing (Mark) Ren, Hao-Hsiang Hsiao, Sung Kyu Lim
NVCell 2: Routability-Driven Standard Cell Layout in Advanced Nodes with Lattice Graph Routability Model
Chia-Tung (Mark) Ho, Alvin Ho, Matt Fojtik, Minsoo Kim, Shang Wei, Yaguang LI, Brucek Khailany, Haoxing (Mark) Ren
AutoDMP: Automated DREAMPlace-based Macro Placement
Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Haoxing (Mark) Ren
On Legalization of Die Bonding Bumps and Pads for 3D ICs
Sai Pentapati, Anthony Agnesina, Moritz Brunion, Yen-Hsiang Huang, Sung Kyu Lim
Joint Neural Denoising of Surfaces and Volumes
Nikolai Hofmann, Jon Hasselgren, Jacob Munkberg
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence
Michael Bauer, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, Alex Aiken
Parsimony: Enabling SIMD/Vector Programming in Standard Compiler Flows
Vijay Kandiah, Daniel Lustig, Oreste Villa, David Nellans, Nikos Hardavellas
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Haoxing (Mark) Ren
Beyond CPO: A Motivation and Approach for Bringing Optics onto the Silicon Interposer
Ben Lee, Nikola Nedovic, Trey Greer, Tom Gray
Target-free Text-guided Image Manipulation
Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavy, Gal Dalal
A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm
Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany
BufFormer: A Generative ML Framework for Scalable Buffering
Rongjian Liang, Siddhartha Nath, Anand Rajaram, Jiang Hu, Haoxing (Mark) Ren
Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System
Rachel Brown, Vasha DuTell, Bruce Walter, Ruth Rosenholtz, Peter Shirley, Morgan McGuire, David Luebke
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning
Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler
Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
Cheng-Yen Hsieh, Chih-Jung Chang, Fu-En Yang, Frank Wang