Chaojian Li | DeepAI

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252 publications
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115 publications
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89 publications
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75 publications
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Yingyan Lin
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∙ 05/09/2023

Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing

Instant on-device Neural Radiance Fields (NeRFs) are in growing demand f...

0 fcq, 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. ∙

∙ 03/19/2023

ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement

Social ambiance describes the context in which social interactions happe...

0 Chaojian Li, et al. ∙

∙ 12/05/2022

INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors

We present a method that accelerates reconstruction of 3D scenes and obj...

4 Chaojian Li, et al. ∙

∙ 12/02/2022

RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering

Neural Radiance Field (NeRF) based rendering has attracted growing atten...

0 Chaojian Li, et al. ∙

∙ 11/09/2022

ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention

Vision Transformer (ViT) has emerged as a competitive alternative to con...

0 Jyotikrishna Dass, et al. ∙

∙ 10/18/2022

ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design

Vision Transformers (ViTs) have achieved state-of-the-art performance on...

0 Haoran You, 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. ∙

∙ 12/21/2021

MIA-Former: Efficient and Robust Vision Transformers via Multi-grained Input-Adaptation

ViTs are often too computationally expensive to be fitted onto real-worl...

15 Zhongzhi Yu, et al. ∙

∙ 11/19/2021

FBNetV5: Neural Architecture Search for Multiple Tasks in One Run

Neural Architecture Search (NAS) has been widely adopted to design accur...

10 Bichen Wu, et al. ∙

∙ 09/11/2021

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency

The recent breakthroughs of deep neural networks (DNNs) and the advent o...

0 Yonggan Fu, et al. ∙

∙ 07/16/2021

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference

Semantic segmentation for scene understanding is nowadays widely demande...

0 Chaojian Li, et al. ∙

∙ 06/11/2021

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning

Driven by the explosive interest in applying deep reinforcement learning...

0 Yonggan Fu, et al. ∙

∙ 04/22/2021

InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks

The promise of Deep Neural Network (DNN) powered Internet of Thing (IoT)...

0 Yonggan Fu, et al. ∙

∙ 03/19/2021

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

HardWare-aware Neural Architecture Search (HW-NAS) has recently gained t...

0 Chaojian Li, et al. ∙

∙ 01/04/2021

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training

The record-breaking performance of deep neural networks (DNNs) comes wit...

5 Xiaohan Chen, et al. ∙

∙ 12/24/2020

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training

Recent breakthroughs in deep neural networks (DNNs) have fueled a tremen...

0 Yonggan Fu, et al. ∙

∙ 10/28/2020

DNA: Differentiable Network-Accelerator Co-Search

Powerful yet complex deep neural networks (DNNs) have fueled a booming d...

0 Yongan Zhang, et al. ∙

∙ 10/24/2020

ShiftAddNet: A Hardware-Inspired Deep Network

Multiplication (e.g., convolution) is arguably a cornerstone of modern d...

0 Haoran You, et al. ∙

∙ 05/07/2020

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

We present SmartExchange, an algorithm-hardware co-design framework to t...

6 fcq, et al. ∙

∙ 03/02/2020

A New MRAM-based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision

The excellent performance of modern deep neural networks (DNNs) comes at...

0 Hongjie Wang, et al. ∙

∙ 02/26/2020

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures

The recent breakthroughs in deep neural networks (DNNs) have spurred a t...

0 fcq, et al. ∙

∙ 01/06/2020

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs

Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a growin...

0 Pengfei Xu, et al. ∙

∙ 09/26/2019

Drawing early-bird tickets: Towards more efficient training of deep networks

(Frankle & Carbin, 2019) shows that there exist winning tickets (small b...

0 Haoran You, et al. ∙