Mingtian Zhang
13 papers · 2020–2026 · 5 venues · across top CS/AI venues
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Research topics
Machine Learning
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Deep Learning
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Optimization & Theory · Machine Learning
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Models
(8)
Artificial Intelligence
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Core Methods
(4)
Bayesian & Probabilistic · Machine Learning
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Core AI
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Learning Types · Machine Learning
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Learning Types · Deep Learning
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Computer Vision
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Bayesian & Probabilistic · Artificial Intelligence
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Optimization & Theory · Deep Learning
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Mathematics & Optimization
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Keywords
probabilistic modeling
(3)
diffusion model
(2)
spread divergence
(2)
generative model
(2)
probabilistic model
(2)
lossless compression
(2)
density estimation
(1)
manifold learning
(1)
sequence modeling
(1)
facial animation
(1)
gaussian splatting
(1)
probability distribution
(1)
intrinsic dimension
(1)
gibbs sampling
(1)
sampling efficiency
(1)
knowledge transfer
(1)
likelihood estimation
(1)
independent components analysis
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direct preference optimization
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active preference learning
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Papers
GaussianHeadTalk: Wobble-Free 3D Talking Heads with Audio Driven Gaussian Splatting
WACV 2026
Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching
ICLR 2025
Training Neural Samplers with Reverse Diffusive KL Divergence
AISTATS 2025
Active Preference Learning for Large Language Models
ICML 2024
Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective
NeurIPS 2024
Diffusive Gibbs Sampling
ICML 2024
Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
NeurIPS 2024
Moment Matching Denoising Gibbs Sampling
NeurIPS 2023
Spread Flows for Manifold Modelling
AISTATS 2023
Generalization Gap in Amortized Inference
NeurIPS 2022
AFEC: Active Forgetting of Negative Transfer in Continual Learning
NeurIPS 2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling
NeurIPS 2021
Spread Divergence
ICML 2020