Anqi Wu
18 papers · 2014–2025 · 6 conferences · across top CS/AI conferences
Achievements
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๐ Academic Marathon (11) ๐งญ Keyword Pioneer ๐ Interdisciplinary Bridge ๐ Conference Polyglot (6) ๐ฃ Hot Topic Early Bird
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Keyword Pioneer
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Cross-Pollinator
(11)
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Conference Polyglot
(6)
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Triple Crown
๐
Keyword Champion
(2)
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Century Club
(18)
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Conference Pioneer
โก
Prolific Year
(5)
๐๏ธ
Keyword Collector
(69)
Conferences
NIPS (8)
ICML (4)
ICLR (3)
IJCAI (1)
JMLR (1)
UAI (1)
Top co-authors
Keywords
gaussian process
(4)
latent variable model
(3)
variational inference
(3)
automatic relevance determination
(2)
latent dynamics
(2)
dimensionality reduction
(2)
hierarchical model
(2)
bayesian inference
(2)
sparse regression
(2)
disentangled representation
(2)
diffusion model
(2)
brain-computer interface
(1)
inverse reinforcement learning
(1)
markov chain monte carlo
(1)
video generation
(1)
neural dynamics
(1)
neural encoding
(1)
motor cortex
(1)
feature selection
(1)
manifold learning
(1)
Papers
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
ICML 2025
Towards Fairness with Limited Demographics via Disentangled Learning
IJCAI 2025
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
ICML 2025
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
ICML 2024
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
ICML 2024
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
NIPS 2024
One-hot Generalized Linear Model for Switching Brain State Discovery
ICLR 2024
Forward $\chi^2$ Divergence Based Variational Importance Sampling
ICLR 2024
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
NIPS 2023
Inverse Reinforcement Learning with the Average Reward Criterion
NIPS 2023
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
NIPS 2020
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
UAI 2019
Deterministic Variational Inference for Robust Bayesian Neural Networks
ICLR 2019
Dependent relevance determination for smooth and structured sparse regression
JMLR 2019
Learning a latent manifold of odor representations from neural responses in piriform cortex
NIPS 2018
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
NIPS 2017
Convolutional spike-triggered covariance analysis for neural subunit models
NIPS 2015
Sparse Bayesian structure learning with โdependent relevance determinationโ priors
NIPS 2014