Cheng Wan | DeepAI

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∙ 09/19/2023

GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models

The remarkable capabilities and intricate nature of Artificial Intellige...

0 Yonggan Fu, et al. ∙

∙ 07/16/2023

3D-Carbon: An Analytical Carbon Modeling Tool for 3D and 2.5D Integrated Circuits

Environmental sustainability, driven by concerns about climate change, r...

0 Yujie Zhao, et al. ∙

∙ 06/24/2023

A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware

Graph neural networks (GNNs) are emerging for machine learning research ...

0 Shichang Zhang, et al. ∙

∙ 04/24/2023

Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction

Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable...

0 Sixu Li, et al. ∙

∙ 07/24/2022

e-G2C: A 0.14-to-8.31 μJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM

This work presents the first silicon-validated dedicated EGM-to-ECG (G2C...

0 fcq, et al. ∙

∙ 06/15/2022

i-FlatCam: A 253 FPS, 91.49 μJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR

We present a first-of-its-kind ultra-compact intelligent camera system, ...

0 fcq, et al. ∙

∙ 06/02/2022

EyeCoD: Eye Tracking System Acceleration via FlatCam-based Algorithm Accelerator Co-Design

Eye tracking has become an essential human-machine interaction modality ...

0 Haoran You, et al. ∙

∙ 06/02/2022

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks

Efficient deep neural network (DNN) models equipped with compact operato...

10 Yonggan Fu, et al. ∙

∙ 03/21/2022

BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling

Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art...

20 Cheng Wan, et al. ∙

∙ 03/20/2022

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication

Graph Convolutional Networks (GCNs) is the state-of-the-art method for l...

7 Cheng Wan, et al. ∙

∙ 03/16/2022

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Vision transformers (ViTs) have recently set off a new wave in neural ar...

5 Yonggan Fu, et al. ∙

∙ 11/21/2019

Efficient Estimation of Equilibria in Large Aggregative Games with Coupling Constraints

Aggregative games have many industrial applications, and computing an eq...

0 Paulin Jacquot, et al. ∙

∙ 08/20/2019

Sensor-Based Estimation of Dim Light Melatonin Onset (DLMO) Using Features of Two Time Scales

Circadian rhythms govern most essential biological processes in the huma...

0 Cheng Wan, et al. ∙

∙ 06/04/2019

Nonatomic Aggregative Games with Infinitely Many Types

We define and analyze the notion of variational Wardrop equilibrium for ...

0 Paulin Jacquot, et al. ∙

∙ 12/05/2018

Peer-to-Peer Electricity Market Analysis: From Variational to Generalized Nash Equilibrium

We consider a network of prosumers involved in peer-to-peer energy excha...

0 Hélène Le Cadre, et al. ∙

∙ 10/02/2018

Efficient Estimation of Equilibria of Large Congestion Games with Heterogeneous Players

Computing an equilibrium in congestion games can be challenging when the...

0 Cheng Wan, et al. ∙

∙ 06/16/2018

Nonsmooth Aggregative Games with Coupling Constraints and Infinitely Many Classes of Players

After defining a pure-action profile in a nonatomic aggregative game, wh...

0 Paulin Jacquot, et al. ∙

∙ 04/09/2018

Routing Game on Parallel Networks: the Convergence of Atomic to Nonatomic

We consider an instance of a nonatomic routing game. We assume that the ...

0 Paulin Jacquot, et al. ∙

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