Jiaxiang Wu
29 papers · 2014–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (10) π Academic Marathon (11) π§ Keyword Pioneer π£ Hot Topic Early Bird π Cross-Pollinator (9)
π
Renaissance Researcher
(10)
πΊοΈ
Taxonomy Completionist
(70)
π
Conference Polyglot
(10)
π€
Dynamic Duo
(10)
π
Grand Slam
π±
Topic Pioneer
ποΈ
Keyword Collector
(123)
π
Century Club
(29)
π
Conference Pioneer
π
Trend Setter
β‘
Prolific Year
(5)
π₯
Unstoppable
(8)
Conferences
AAAI (7)
ICML (6)
CVPR (5)
ICLR (4)
NIPS (2)
AISTATS (1)
ECCV (1)
EMNLP (1)
ICCV (1)
JMLR (1)
Top co-authors
Research topics
Keywords
model compression
(5)
knowledge distillation
(4)
distributed optimization
(3)
face recognition
(3)
few-shot learning
(2)
convolutional neural network
(2)
neural architecture search
(2)
communication efficiency
(2)
gradient quantization
(2)
graph neural network
(2)
approximate nearest neighbor
(2)
3d reconstruction
(1)
adversarial robustness
(1)
online learning
(1)
semi-supervised learning
(1)
image classification
(1)
dimensionality reduction
(1)
zero-shot learning
(1)
ensemble learning
(1)
catastrophic forgetting
(1)
Papers
IgGM: A Generative Model for Functional Antibody and Nanobody Design
ICLR 2025
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
ICML 2024
EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model
ICLR 2024
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery β a Focus on Affinity Prediction Problems with Noise Annotations
AAAI 2023
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection
EMNLP 2023
Privacy-Preserving Face Recognition Using Random Frequency Components
ICCV 2023
Probabilistic Knowledge Distillation of Face Ensembles
CVPR 2023
Towards Stable Test-time Adaptation in Dynamic Wild World
ICLR 2023
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
ICLR 2022
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks
AAAI 2022
Self-Supervised Pre-training for Protein Embeddings Using Tertiary Structures
AAAI 2022
Efficient Test-Time Model Adaptation without Forgetting
ICML 2022
Evaluation-Oriented Knowledge Distillation for Deep Face Recognition
CVPR 2022
Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain
ECCV 2022
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning
AAAI 2021
AdaXpert: Adapting Neural Architecture for Growing Data
ICML 2021
Revisiting Parameter Sharing for Automatic Neural Channel Number Search
NIPS 2020
Few Shot Network Compression via Cross Distillation
AAAI 2020
M-NAS: Meta Neural Architecture Search
AAAI 2020
Double Quantization for Communication-Efficient Distributed Optimization
NIPS 2019
An Efficient Approach to Informative Feature Extraction from Multimodal Data
AAAI 2019
Exploring Fast and Communication-Efficient Algorithms in Large-Scale Distributed Networks
AISTATS 2019
Collaborative Channel Pruning for Deep Networks
ICML 2019
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
ICML 2018
Quantized Convolutional Neural Networks for Mobile Devices
CVPR 2016
Online Sketching Hashing
CVPR 2015
Hashing for Distributed Data
ICML 2015
Bayesian Co-Boosting for Multi-modal Gesture Recognition
JMLR 2014
Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction
CVPR 2014