Robert Kirby
16 papers · 2018–2024 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (36) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π§
Keyword Pioneer
π€
Dynamic Duo
(15)
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Conference Pioneer
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
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Century Club Β· Bronze
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Trend Setter
ποΈ
Keyword Collector
(67)
Top co-authors
Research topics
Machine Learning
(15)
Core Methods
(9)
Optimization & Theory
(8)
Learning Types
(7)
Artificial Intelligence
(6)
Deep Learning
(5)
Mathematics & Optimization
(5)
Bayesian & Probabilistic Β· Machine Learning
(5)
Optimization
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Models
(3)
Application Areas
(2)
Architectures
(2)
Core AI
(2)
Learning Paradigms
(2)
Keywords
gaussian process
(7)
variational inference
(6)
mutual information
(3)
uncertainty quantification
(3)
acquisition function
(3)
active learning
(2)
deep neural network
(2)
temporal dynamics
(2)
physics-informed learning
(2)
partial differential equation
(2)
differential equation
(2)
multi-fidelity modeling
(2)
bayesian optimization
(2)
tensor decomposition
(2)
bayesian inference
(2)
multi-fidelity optimization
(2)
deep kernel learning
(1)
loss landscape
(1)
nonparametric bayesian
(1)
few-shot learning
(1)
Papers
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels
AISTATS 2024
Multi-Resolution Active Learning of Fourier Neural Operators
AISTATS 2024
Meta-Learning with Adjoint Methods
AISTATS 2023
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
ICML 2022
Batch Multi-Fidelity Active Learning with Budget Constraints
NeurIPS 2022
Bayesian Continuous-Time Tucker Decomposition
ICML 2022
Decomposing Temporal High-Order Interactions via Latent ODEs
ICML 2022
Deep Multi-Fidelity Active Learning of High-Dimensional Outputs
AISTATS 2022
Infinite-Fidelity Coregionalization for Physical Simulation
NeurIPS 2022
Physics Informed Deep Kernel Learning
AISTATS 2022
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
NeurIPS 2021
Characterizing possible failure modes in physics-informed neural networks
NeurIPS 2021
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
AISTATS 2021
Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations
AAAI 2020
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
NeurIPS 2020
SDC-Net: Video prediction using spatially-displaced convolution
ECCV 2018