Yuyang Wang
25 papers · 2012–2026 · 13 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (48) π Conference Polyglot Β· Gold π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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(8)
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(114)
Venues
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Machine Learning
(19)
Deep Learning
(14)
Optimization & Theory
(11)
Data Science & Analytics
(9)
Core Methods
(9)
Models
(8)
Artificial Intelligence
(7)
Methods
(7)
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(5)
Learning Types Β· Machine Learning
(5)
Core AI
(4)
Learning Types Β· Deep Learning
(4)
Computer Vision
(3)
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(3)
Keywords
time series forecasting
(6)
deep learning
(3)
neural network
(3)
diffusion model
(3)
recurrent neural network
(3)
probabilistic forecasting
(3)
graph neural network
(2)
probabilistic forecast
(2)
quantile regression
(2)
deep neural network
(2)
adversarial robustness
(2)
transfer learning
(2)
uncertainty quantification
(2)
wasserstein distance
(2)
time series
(2)
generative model
(2)
recommender system
(2)
anomaly detection
(1)
domain adaptation
(1)
autoregressive transformer
(1)
Papers
An Exponential Lower Bound for Spectral Density Estimation on Unweighted Graphs
COLT 2026
QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis
ACL 2026
STARFlow-V: End-to-End Video Generative Modeling with Autoregressive Normalizing Flows
CVPR 2026
CAGCRN: Real-Time Speech Enhancement with a Lightweight Model for Joint Acoustic Echo Cancellation and Noise Suppression
Interspeech 2025
Denoising Autoregressive Transformers for Scalable Text-to-Image Generation
ICLR 2025
INRFlow: Flow Matching for INRs in Ambient Space
ICML 2025
ReAgent: Reversible Multi-Agent Reasoning for Knowledge-Enhanced Multi-Hop QA
EMNLP 2025
Manifold Diffusion Fields
ICLR 2024
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
ICML 2024
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI
AISTATS 2023
Coherent Probabilistic Forecasting of Temporal Hierarchies
AISTATS 2023
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
AAAI 2022
Domain Adaptation for Time Series Forecasting via Attention Sharing
ICML 2022
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
AISTATS 2022
Robust Probabilistic Time Series Forecasting
AISTATS 2022
Adversarially Robust Imitation Learning
CoRL 2021
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
L4DC 2021
Correcting Exposure Bias for Link Recommendation
ICML 2021
Variance Reduced Training with Stratified Sampling for Forecasting Models
ICML 2021
GluonTS: Probabilistic and Neural Time Series Modeling in Python
JMLR 2020
Deep Factors for Forecasting
ICML 2019
Probabilistic Forecasting with Spline Quantile Function RNNs
AISTATS 2019
Deep State Space Models for Time Series Forecasting
NeurIPS 2018
Sparse Variational Inference for Generalized GP Models
ICML 2015
Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions
COLT 2012