Yutian Chen
29 papers · 2010–2024 · 8 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Conference Polyglot (8) πΊοΈ Taxonomy Completionist (16) π§ Keyword Pioneer π Academic Marathon (14)
π
Interdisciplinary Bridge
π
Conference Polyglot
(8)
π
Academic Marathon
(14)
π
Grand Slam
π₯
Mega-Team
(20)
ποΈ
Keyword Collector
(101)
π
Trend Setter
π
Century Club
(29)
π₯
Unstoppable
(12)
π
Conference Pioneer
Conferences
ICML (8)
ICLR (6)
NIPS (5)
AISTATS (3)
JMLR (3)
ECCV (2)
AAAI (1)
EMNLP (1)
Top co-authors
Keywords
bayesian inference
(4)
neural network
(3)
gaussian process
(3)
variational inference
(3)
bayesian optimization
(2)
parallel computation
(2)
markov random field
(2)
reinforcement learning
(2)
dynamical system
(2)
parallel sampling
(2)
markov chain monte carlo
(2)
state-space model
(2)
transfer learning
(1)
dirichlet process
(1)
black-box optimization
(1)
policy optimization
(1)
few-shot learning
(1)
continual learning
(1)
online learning
(1)
hyperparameter optimization
(1)
Papers
Event-Based Motion Magnification
ECCV 2024
$\pi$2vec: Policy Representation with Successor Features
ICLR 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
Token Prediction as Implicit Classification to Identify LLM-Generated Text
EMNLP 2023
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
Importance Weighted Kernel Bayesβ Rule
ICML 2022
Introducing Symmetries to Black Box Meta Reinforcement Learning
AAAI 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
NIPS 2022
On Instrumental Variable Regression for Deep Offline Policy Evaluation
JMLR 2022
Benchmarks for Deep Off-Policy Evaluation
ICLR 2021
Active Offline Policy Selection
NIPS 2021
Learning Deep Features in Instrumental Variable Regression
ICLR 2021
Modular Meta-Learning with Shrinkage
NIPS 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
Scalable Discrete Sampling as a Multi-Armed Bandit Problem
ICML 2016
Herded Gibbs Sampling
JMLR 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
NIPS 2014
Evidence Estimation for Bayesian Partially Observed MRFs
AISTATS 2013
Distributed and Adaptive Darting Monte Carlo through Regenerations
AISTATS 2013
Parametric Herding
AISTATS 2010
On Herding and the Perceptron Cycling Theorem
NIPS 2010