David Bindel
14 papers · 2015–2025 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (31)
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Keyword Collector
(72)
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Trend Setter
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Renaissance Researcher
(6)
Top co-authors
Research topics
Machine Learning
(11)
Optimization & Theory
(9)
Artificial Intelligence
(7)
Bayesian & Probabilistic Β· Artificial Intelligence
(7)
Core Methods
(6)
Deep Learning
(3)
Mathematics & Optimization
(3)
Natural Language Processing
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Computer Vision
(2)
Analysis
(2)
Applications
(2)
Mathematics
(2)
Optimization
(2)
Data Science & Analytics
(1)
Keywords
gaussian process
(6)
bayesian optimization
(4)
spectral algorithm
(2)
latent topic analysis
(2)
kernel learning
(2)
topic inference
(2)
spectral topic model
(2)
variational inference
(2)
matrix factorization
(2)
global optimization
(1)
bayesian inference
(1)
non-convex optimization
(1)
rotation averaging
(1)
gaussian process regression
(1)
manifold optimization
(1)
topic modeling
(1)
spectral analysis
(1)
gaussian processes
(1)
kernel matrix
(1)
exploration exploitation
(1)
Papers
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
ICML 2025
Surveillance Evasion Through Bayesian Reinforcement Learning
AISTATS 2023
Variational Gaussian Processes with Decoupled Conditionals
NeurIPS 2023
On-the-fly Rectification for Robust Large-Vocabulary Topic Inference
ICML 2021
Scaling Gaussian Processes with Derivative Information Using Variational Inference
NeurIPS 2021
Efficient Rollout Strategies for Bayesian Optimization
UAI 2020
On the Distribution of Minima in Intrinsic-Metric Rotation Averaging
CVPR 2020
Prior-aware Composition Inference for Spectral Topic Models
AISTATS 2020
Randomly Projected Additive Gaussian Processes for Regression
ICML 2020
Practical Correlated Topic Modeling and Analysis via the Rectified Anchor Word Algorithm
EMNLP 2019
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
NeurIPS 2018
Scaling Gaussian Process Regression with Derivatives
NeurIPS 2018
Scalable Log Determinants for Gaussian Process Kernel Learning
NeurIPS 2017
Robust Spectral Inference for Joint Stochastic Matrix Factorization
NeurIPS 2015