b'Jiaqi Gu'

research

∙ 05/31/2023

Integrated multi-operand optical neurons for scalable and hardware-efficient deep learning

The optical neural network (ONN) is a promising hardware platform for ne...

0 Chenghao Feng, et al. ∙

research

∙ 05/31/2023

DOTA: A Dynamically-Operated Photonic Tensor Core for Energy-Efficient Transformer Accelerator

The wide adoption and significant computing resource consumption of atte...

0 Hanqing Zhu, et al. ∙

research

∙ 05/31/2023

M3ICRO: Machine Learning-Enabled Compact Photonic Tensor Core based on PRogrammable Multi-Operand Multimode Interference

Photonic computing shows promise for transformative advancements in mach...

0 Jiaqi Gu, et al. ∙

research

∙ 05/24/2023

Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers

Transformers have achieved great success in machine learning application...

0 Zixuan Jiang, et al. ∙

research

∙ 11/30/2022

HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression

Transformers have attained superior performance in natural language proc...

17 Jiaqi Gu, et al. ∙

research

∙ 10/30/2022

QuEst: Graph Transformer for Quantum Circuit Reliability Estimation

Among different quantum algorithms, PQC for QML show promises on near-te...

0 Hanrui Wang, et al. ∙

research

∙ 09/19/2022

NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation

Optical computing is an emerging technology for next-generation efficien...

1 Jiaqi Gu, et al. ∙

research

∙ 08/17/2022

Fuse and Mix: MACAM-Enabled Analog Activation for Energy-Efficient Neural Acceleration

Analog computing has been recognized as a promising low-power alternativ...

0 Hanqing Zhu, et al. ∙

research

∙ 07/30/2022

Delving into Effective Gradient Matching for Dataset Condensation

As deep learning models and datasets rapidly scale up, network training ...

0 Zixuan Jiang, et al. ∙

research

∙ 07/13/2022

RobustAnalog: Fast Variation-Aware Analog Circuit Design Via Multi-task RL

Analog/mixed-signal circuit design is one of the most complex and time-c...

1 Wei Shi, et al. ∙

research

∙ 06/02/2022

Universal Polar Coding for Parallel Gaussian Channels with Non-Binary Inputs and Its Applications to HARQ and MIMO

In this paper, we first propose an universal polar coding scheme for par...

0 Bin Li, et al. ∙

research

∙ 04/02/2022

Homography Loss for Monocular 3D Object Detection

Monocular 3D object detection is an essential task in autonomous driving...

5 Jiaqi Gu, et al. ∙

research

∙ 03/13/2022

CVFNet: Real-time 3D Object Detection by Learning Cross View Features

In recent years 3D object detection from LiDAR point clouds has made gre...

0 Jiaqi Gu, et al. ∙

research

∙ 02/26/2022

QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning

Parameterized Quantum Circuits (PQC) are drawing increasing research int...

0 Hanrui Wang, et al. ∙

research

∙ 12/15/2021

ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement

With the recent advances in optical phase change material (PCM), photoni...

0 Hanqing Zhu, et al. ∙

research

∙ 11/11/2021

Silicon photonic subspace neural chip for hardware-efficient deep learning

As deep learning has shown revolutionary performance in many artificial ...

0 Chenghao Feng, et al. ∙

research

∙ 11/01/2021

HRViT: Multi-Scale High-Resolution Vision Transformer

Vision transformers (ViTs) have attracted much attention for their super...

0 Jiaqi Gu, et al. ∙

research

∙ 10/27/2021

L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization

Silicon-photonics-based optical neural network (ONN) is a promising hard...

0 Jiaqi Gu, et al. ∙

research

∙ 10/21/2021

RoQNN: Noise-Aware Training for Robust Quantum Neural Networks

Quantum Neural Network (QNN) is a promising application towards quantum ...

0 Hanrui Wang, et al. ∙

research

∙ 10/04/2021

A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms

Discrete cosine transform (DCT) and other Fourier-related transforms hav...

0 Zixuan Jiang, et al. ∙

research

∙ 08/28/2021

DenseLiDAR: A Real-Time Pseudo Dense Depth Guided Depth Completion Network

Depth Completion can produce a dense depth map from a sparse input and p...

57 Jiaqi Gu, et al. ∙

research

∙ 08/25/2021

Towards Memory-Efficient Neural Networks via Multi-Level in situ Generation

Deep neural networks (DNN) have shown superior performance in a variety ...

0 Jiaqi Gu, et al. ∙

research

∙ 07/22/2021

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (...

40 Hanrui Wang, et al. ∙

research

∙ 04/15/2021

Performance of CRC Concatenated Pre-transformed RM-Polar Codes

In this paper, we discuss pre-transformed RM-Polar codes and cyclic redu...

0 Bin Li, et al. ∙

research

∙ 04/01/2021

Optimizer Fusion: Efficient Training with Better Locality and Parallelism

Machine learning frameworks adopt iterative optimizers to train neural n...

0 Zixuan Jiang, et al. ∙

research

∙ 02/10/2021

Bayesian Knockoff Filter Using Gibbs Sampler

In many fields, researchers are interested in discovering features with ...

0 Jiaqi Gu, et al. ∙

research

∙ 12/21/2020

Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization

Optical neural networks (ONNs) have demonstrated record-breaking potenti...

0 Jiaqi Gu, et al. ∙

research

∙ 11/20/2020

Reconstruct Kaplan–Meier Estimator as M-estimator and Its Confidence Band

The Kaplan–Meier (KM) estimator, which provides a nonparametric estimate...

0 Jiaqi Gu, et al. ∙

research

∙ 12/13/2019

On Pre-transformed Polar Codes

In this paper, we prove that any pre-transformation with an upper-triang...

0 Bin Li, et al. ∙

research

∙ 10/20/2019

Monotonic Properties of Completed Aggregates in Recursive Queries

The use of aggregates in recursion enables efficient and scalable suppor...

0 Carlo Zaniolo, et al. ∙

Jiaqi Gu

Featured Co-authors