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09/13/2023
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction
Magnetic resonance imaging (MRI) plays an important role in modern medic...
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07/25/2023
One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction
Magnetic resonance imaging (MRI) is a principal radiological modality th...
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07/17/2023
HeroLT: Benchmarking Heterogeneous Long-Tailed Learning
Long-tailed data distributions are prevalent in a variety of domains, in...
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06/20/2023
On Evaluating Multilingual Compositional Generalization with Translated Datasets
Compositional generalization allows efficient learning and human-like in...
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05/30/2023
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
Large language models (LLMs) can learn to perform a wide range of natura...
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05/29/2023
Gaussian Process Probes (GPP) for Uncertainty-Aware Probing
Understanding which concepts models can and cannot represent has been fu...
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05/25/2023
Dynamic Enhancement Network for Partial Multi-modality Person Re-identification
Many existing multi-modality studies are based on the assumption of moda...
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05/25/2023
Rethink Diversity in Deep Learning Testing
Deep neural networks (DNNs) have demonstrated extraordinary capabilities...
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05/23/2023
Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification
Multi-spectral vehicle re-identification aims to address the challenge o...
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04/24/2023
Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Driving
Cooperative perception enabled by V2X Communication technologies can sig...
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03/17/2023
TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
Vision-centric joint perception and prediction (PnP) has become an emerg...
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02/21/2023
Oriented Object Detection in Optical Remote Sensing Images: A Survey
Oriented object detection is one of the most fundamental and challenging...
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12/23/2022
Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints
Recently, unsupervised domain adaptation in satellite pose estimation ha...
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12/20/2022
HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
Bayesian optimization (BO), while proved highly effective for many black...
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10/23/2022
A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
Recent deep learning is superior in providing high-quality images and ul...
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10/20/2022
Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence
In this work, we propose a Physics-Informed Deep Diffusion magnetic reso...
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10/11/2022
Parallel Augmentation and Dual Enhancement for Occluded Person Re-identification
Occluded person re-identification (Re-ID), the task of searching for the...
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07/07/2022
Pre-training helps Bayesian optimization too
Bayesian optimization (BO) has become a popular strategy for global opti...
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05/26/2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
Meta-learning hyperparameter optimization (HPO) algorithms from prior ex...
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04/14/2022
Ear Wearable (Earable) User Authentication via Acoustic Toothprint
Earables (ear wearables) is rapidly emerging as a new platform encompass...
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03/21/2022
Physics-driven Synthetic Data Learning for Biomedical Magnetic Resonance
Deep learning has innovated the field of computational imaging. One of i...
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03/15/2022
DialogueNeRF: Towards Realistic Avatar Face-to-face Conversation Video Generation
Conversation is an essential component of virtual avatar activities in t...
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03/02/2022
A Quantitative Geometric Approach to Neural Network Smoothness
Fast and precise Lipschitz constant estimation of neural networks is an ...
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12/29/2021
Onsite Non-Line-of-Sight Imaging via Online Calibrations
There has been an increasing interest in deploying non-line-of-sight (NL...
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12/09/2021
One-dimensional Deep Low-rank and Sparse Network for Accelerated MRI
Deep learning has shown astonishing performance in accelerated magnetic ...
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09/16/2021
Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers
The performance of deep neural networks can be highly sensitive to the c...
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08/11/2021
An Ear Canal Deformation Based User Authentication Using Ear Wearable Devices
Biometric-based authentication is gaining increasing attention for weara...
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06/07/2021
Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Knowledge distillation (KD) is a successful approach for deep neural net...
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06/02/2021
Acoustic-based Object Detection for Pedestrian Using Smartphone
Walking while using a smartphone is becoming a major pedestrian safety c...
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04/10/2021
Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis
Knowledge distillation (KD) has proved to be an effective approach for d...
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04/08/2021
Convolutional Neural Network Pruning with Structural Redundancy Reduction
Convolutional neural network (CNN) pruning has become one of the most su...
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02/14/2021
Exploring Adversarial Robustness of Deep Metric Learning
Deep Metric Learning (DML), a widely-used technique, involves learning a...
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01/02/2021
Non-line-of-Sight Imaging via Neural Transient Fields
We present a neural modeling framework for Non-Line-of-Sight (NLOS) imag...
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12/29/2020
Accelerated NMR Spectroscopy: Merge Optimization with Deep Learning
Multi-dimensional NMR spectroscopy is an invaluable biophysical tool in ...
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08/14/2020
A Note on the Likelihood Ratio Test in High-Dimensional Exploratory Factor Analysis
The likelihood ratio test is widely used in exploratory factor analysis ...
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07/12/2020
Abstract Universal Approximation for Neural Networks
With growing concerns about the safety and robustness of neural networks...
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06/08/2020
Learning compositional models of robot skills for task and motion planning
The objective of this work is to augment the basic abilities of a robot ...
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04/29/2020
TOFU: Target-Oriented FUzzer
Program fuzzing—providing randomly constructed inputs to a computer prog...
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04/29/2020
TOFU:Target-Orienter FUzzer
Program fuzzing-providing randomly constructed inputs to a computer prog...
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02/07/2020
Semantic Robustness of Models of Source Code
Deep neural networks are vulnerable to adversarial examples - small inpu...
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01/13/2020
Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy
Since the concept of deep learning (DL) was formally proposed in 2006, i...
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05/16/2019
Investigating Channel Pruning through Structural Redundancy Reduction - A Statistical Study
Most existing channel pruning methods formulate the pruning task from a ...
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02/18/2019
Speeding up convolutional networks pruning with coarse ranking
Channel-based pruning has achieved significant successes in accelerating...
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02/18/2019
Single-shot Channel Pruning Based on Alternating Direction Method of Multipliers
Channel pruning has been identified as an effective approach to construc...
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11/23/2018
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Bayesian optimization usually assumes that a Bayesian prior is given. Ho...
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10/26/2018
Learning sparse relational transition models
We present a representation for describing transition models in complex ...
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07/26/2018
Learning to guide task and motion planning using score-space representation
In this paper, we propose a learning algorithm that speeds up the search...
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05/05/2018
Fast-converging Conditional Generative Adversarial Networks for Image Synthesis
Building on top of the success of generative adversarial networks (GANs)...
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03/02/2018
Active model learning and diverse action sampling for task and motion planning
The objective of this work is to augment the basic abilities of a robot ...
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01/14/2018