Xinwei Sun
25 papers · 2016–2025 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (53) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Dynamic Duo
(13)
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(3)
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Triple Crown
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Deep Specialist
(11)
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Renaissance Researcher
(6)
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Unstoppable Β· Bronze
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The Questioner
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(138)
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Research topics
Machine Learning
(20)
Artificial Intelligence
(13)
Core AI
(12)
Learning Types
(11)
Optimization & Theory
(9)
Core Methods
(8)
Deep Learning
(6)
Healthcare & Medicine
(5)
Knowledge & Reasoning
(5)
Application Areas
(5)
Clinical
(5)
Reasoning
(5)
Computer Vision
(4)
Mathematics & Optimization
(3)
Domain-Specific
(3)
Keywords
causal inference
(5)
differential inclusion
(3)
medical imaging
(3)
causal discovery
(3)
domain generalization
(3)
proxy variable
(3)
variable splitting
(2)
causal invariance
(2)
variational autoencoder
(2)
disease forecasting
(2)
structural sparsity
(2)
variational inference
(2)
spurious correlation
(2)
disease diagnosis
(2)
time series
(2)
generative model
(2)
domain adaptation
(1)
transfer learning
(1)
feature learning
(1)
ordinal regression
(1)
Papers
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
ICLR 2025
A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging Analysis
AISTATS 2025
Bayesian Active Learning for Bivariate Causal Discovery
ICML 2025
Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond
ICML 2025
Learning Causal Alignment for Reliable Disease Diagnosis
ICLR 2025
Causal Discovery via Conditional Independence Testing with Proxy Variables
ICML 2024
Doubly Robust Proximal Causal Learning for Continuous Treatments
ICLR 2024
Exploring High-dimensional Search Space via Voronoi Graph Traversing
UAI 2024
A New Causal Decomposition Paradigm towards Health Equity
AISTATS 2023
Causal Discovery from Subsampled Time Series with Proxy Variables
NeurIPS 2023
Learning Domain-Agnostic Representation for Disease Diagnosis
ICLR 2023
Out-of-distribution Representation Learning for Time Series Classification
ICLR 2023
Which Invariance Should We Transfer? A Causal Minimax Learning Approach
ICML 2023
Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels
CVPR 2022
Causal Hidden Markov Model for Time Series Disease Forecasting
CVPR 2021
Forecasting Irreversible Disease via Progression Learning
CVPR 2021
Learning Causal Semantic Representation for Out-of-Distribution Prediction
NeurIPS 2021
Recovering Latent Causal Factor for Generalization to Distributional Shifts
NeurIPS 2021
DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths
ICML 2020
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
ECCV 2020
Cascaded Generative and Discriminative Learning for Microcalcification Detection in Breast Mammograms
CVPR 2019
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
NeurIPS 2019
Learning With Unsure Data for Medical Image Diagnosis
ICCV 2019
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
ICML 2018
Split LBI: An Iterative Regularization Path with Structural Sparsity
NeurIPS 2016