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Yexiang Xue

27 papers · 2015–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (55) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (10) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (12) πŸ† Keyword Champion πŸ”₯ Unstoppable (11) πŸ’Ž Century Club (27) ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (135)

Conferences

AAAI (7) IJCAI (6) ICML (4) UAI (4) NIPS (3) EMNLP (1) JMLR (1) NAACL (1)

Top co-authors

Nan Jiang (9) Md Nasim (5) Fan Ding (4) Bart Selman (4) Carla P. Gomes (4) Stefano Ermon (3) Anter El-Azab (2) Jianzhu Ma (2) Maosen Zhang (2) Xinghang Zhang (2)

Keywords

partial differential equation (3) constraint satisfaction (3) neural network (3) symbolic regression (3) probabilistic inference (3) stochastic optimization (2) contrastive divergence (2) approximation algorithm (2) xor sampling (2) markov random field (2) symbolic reasoning (2) random projection (2) sparse decomposition (2) maximum entropy (1) probabilistic modeling (1) compressed sensing (1) statistical inference (1) feature learning (1) representation learning (1) active learning (1)

Papers

Integrating Symbolic Reasoning into Neural Generative Models for Design Generation AAAI 2025
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching AAAI 2025
Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits ICML 2025
Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees AAAI 2024
End-to-End Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning AAAI 2024
Vertical Symbolic Regression via Deep Policy Gradient IJCAI 2024
Racing Control Variable Genetic Programming for Symbolic Regression AAAI 2024
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains AAAI 2024
Natural Language-based State Representation in Deep Reinforcement Learning NAACL 2024
Learning Markov Random Fields for Combinatorial Structures via Sampling through LovΓ‘sz Local Lemma AAAI 2023
Efficient learning of sparse and decomposable PDEs using random projection UAI 2022
X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning UAI 2022
Constraint Reasoning Embedded Structured Prediction JMLR 2022
XOR-CD: Linearly Convergent Constrained Structure Generation ICML 2021
LSH-SMILE: Locality Sensitive Hashing Accelerated Simulation and Learning NIPS 2021
XOR-SGD: provable convex stochastic optimization for decision-making under uncertainty UAI 2021
PALM: Probabilistic area loss Minimization for Protein Sequence Alignment UAI 2021
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach EMNLP 2020
Embedding Conjugate Gradient in Learning Random Walks for Landscape Connectivity Modeling in Conservation IJCAI 2020
Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks IJCAI 2019
Expanding Holographic Embeddings for Knowledge Completion NIPS 2018
End-to-End Learning for the Deep Multivariate Probit Model ICML 2018
XOR-Sampling for Network Design with Correlated Stochastic Events IJCAI 2017
Deep Multi-species Embedding IJCAI 2017
Solving Marginal MAP Problems with NP Oracles and Parity Constraints NIPS 2016
Variable Elimination in the Fourier Domain ICML 2016
Uncovering Hidden Structure through Parallel Problem Decomposition for the Set Basis Problem: Application to Materials Discovery IJCAI 2015