Yutian Chen
30 papers · 2010–2026 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (60) π Conference Polyglot Β· Silver π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Deep Specialist
(10)
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Grand Slam
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Mega-Team Β· Squad
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Keyword Champion
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Keyword Pioneer
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Trend Setter
π
Conference Pioneer
ποΈ
Keyword Collector
(140)
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Unstoppable Β· Silver
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Century Club Β· Bronze
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Renaissance Researcher
(6)
Top co-authors
Research topics
Machine Learning
(26)
Optimization & Theory
(18)
Artificial Intelligence
(17)
Learning Types
(10)
Deep Learning
(9)
Core AI
(8)
Learning Paradigms Β· Artificial Intelligence
(8)
Architectures
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Bayesian & Probabilistic Β· Machine Learning
(5)
Core Methods
(5)
Learning Paradigms Β· Machine Learning
(5)
Computer Vision
(4)
Reinforcement Learning
(4)
Methods
(4)
Keywords
bayesian inference
(4)
black-box optimization
(3)
variational inference
(3)
neural network
(3)
gaussian process
(3)
few-shot learning
(3)
dynamical system
(2)
bayesian optimization
(2)
autoregressive model
(2)
reinforcement learning
(2)
image generation
(2)
meta learning
(2)
markov random field
(2)
state space model
(2)
continuous control
(2)
density estimation
(2)
off-policy evaluation
(2)
causal inference
(2)
markov chain monte carlo
(2)
policy selection
(2)
Papers
Co-Me: Confidence Guided Token Merging for Visual Geometric Transformers
CVPR 2026
Ο2vec: Policy Representation with Successor Features
ICLR 2024
Event-Based Motion Magnification
ECCV 2024
Position: Leverage Foundational Models for Black-Box Optimization
ICML 2024
TimeLens-XL: Real-time Event-based Video Frame Interpolation with Large Motion
ECCV 2024
Discovering Evolution Strategies via Meta-Black-Box Optimization
ICLR 2023
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
JMLR 2023
Token Prediction as Implicit Classification to Identify LLM-Generated Text
EMNLP 2023
Importance Weighted Kernel Bayesβ Rule
ICML 2022
Introducing Symmetries to Black Box Meta Reinforcement Learning
AAAI 2022
On Instrumental Variable Regression for Deep Offline Policy Evaluation
JMLR 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
NeurIPS 2022
Active Offline Policy Selection
NeurIPS 2021
Benchmarks for Deep Off-Policy Evaluation
ICLR 2021
Learning Deep Features in Instrumental Variable Regression
ICLR 2021
Modular Meta-Learning with Shrinkage
NeurIPS 2020
Sample Efficient Adaptive Text-to-Speech
ICLR 2019
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions
ICLR 2018
Learning to Learn without Gradient Descent by Gradient Descent
ICML 2017
Parallel Multiscale Autoregressive Density Estimation
ICML 2017
Herded Gibbs Sampling
JMLR 2016
Scalable Discrete Sampling as a Multi-Armed Bandit Problem
ICML 2016
Distributed Inference for Dirichlet Process Mixture Models
ICML 2015
Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data
ICML 2015
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget
ICML 2014
Variational Gaussian Process State-Space Models
NeurIPS 2014
Distributed and Adaptive Darting Monte Carlo through Regenerations
AISTATS 2013
Evidence Estimation for Bayesian Partially Observed MRFs
AISTATS 2013
On Herding and the Perceptron Cycling Theorem
NeurIPS 2010
Parametric Herding
AISTATS 2010