Yuyang Wang
22 papers · 2012–2026 · 11 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (10) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (12) π§ Keyword Pioneer π Academic Marathon (13)
π
Academic Marathon
(13)
π
Interdisciplinary Bridge
π
Conference Polyglot
(10)
π±
Topic Pioneer
π
Grand Slam
ποΈ
Keyword Collector
(73)
π
Century Club
(21)
π₯
Unstoppable
(8)
π
Trend Setter
β
The Questioner
Conferences
ICML (7)
AISTATS (5)
ICLR (2)
AAAI (1)
ACL (1)
COLT (1)
CORL (1)
EMNLP (1)
JMLR (1)
L4DC (1)
NIPS (1)
Top co-authors
Research topics
Keywords
time series forecasting
(6)
probabilistic forecasting
(3)
neural network
(3)
recurrent neural network
(3)
deep learning
(3)
uncertainty quantification
(2)
transfer learning
(2)
recommender system
(2)
probabilistic forecast
(2)
adversarial robustness
(2)
deep neural network
(2)
quantile regression
(2)
time series
(2)
self-supervised learning
(1)
probabilistic modeling
(1)
bayesian inference
(1)
anomaly detection
(1)
online learning
(1)
stochastic gradient descent
(1)
gaussian process
(1)
Papers
QA-MoE: Towards a Continuous Reliability Spectrum with Quality-Aware Mixture of Experts for Robust Multimodal Sentiment Analysis
ACL 2026
Denoising Autoregressive Transformers for Scalable Text-to-Image Generation
ICLR 2025
ReAgent: Reversible Multi-Agent Reasoning for Knowledge-Enhanced Multi-Hop QA
EMNLP 2025
INRFlow: Flow Matching for INRs in Ambient Space
ICML 2025
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
ICML 2024
Manifold Diffusion Fields
ICLR 2024
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI
AISTATS 2023
Coherent Probabilistic Forecasting of Temporal Hierarchies
AISTATS 2023
Domain Adaptation for Time Series Forecasting via Attention Sharing
ICML 2022
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
AAAI 2022
Robust Probabilistic Time Series Forecasting
AISTATS 2022
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
AISTATS 2022
Adversarially Robust Imitation Learning
CORL 2021
Correcting Exposure Bias for Link Recommendation
ICML 2021
Variance Reduced Training with Stratified Sampling for Forecasting Models
ICML 2021
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
L4DC 2021
GluonTS: Probabilistic and Neural Time Series Modeling in Python
JMLR 2020
Probabilistic Forecasting with Spline Quantile Function RNNs
AISTATS 2019
Deep Factors for Forecasting
ICML 2019
Deep State Space Models for Time Series Forecasting
NIPS 2018
Sparse Variational Inference for Generalized GP Models
ICML 2015
Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions
COLT 2012