Amos J. Storkey
17 papers · 2006–2022 · 1 venue · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (57) π£ Hot Topic Early Bird π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Gold π Keyword Champion
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Keyword Pioneer
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Keyword Trendsetter Combo
(13)
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Trend Setter
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(7)
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Century Club Β· Bronze
ποΈ
Keyword Collector
(135)
Venues
Top co-authors
Research topics
Machine Learning
(17)
Artificial Intelligence
(10)
Learning Types
(10)
Bayesian & Probabilistic Β· Machine Learning
(9)
Optimization & Theory
(8)
Bayesian & Probabilistic Β· Artificial Intelligence
(7)
Interdisciplinary
(5)
Core Methods
(5)
Science
(5)
Deep Learning
(4)
Healthcare & Medicine
(4)
Mathematics & Optimization
(4)
Application Areas
(4)
Learning Paradigms
(4)
Clinical
(3)
Keywords
bayesian inference
(5)
stochastic differential equation
(3)
few-shot learning
(3)
knowledge distillation
(2)
model compression
(2)
causal inference
(2)
generative model
(2)
model distillation
(2)
neural modeling
(2)
functional magnetic resonance imaging
(2)
probabilistic inference
(2)
markov chain monte carlo
(2)
neural network
(2)
domain adaptation
(2)
deep boltzmann machine
(2)
fmri analysis
(2)
parameter estimation
(2)
bayesian learning
(1)
stochastic gradient
(1)
approximate inference
(1)
Papers
Hamiltonian Latent Operators for content and motion disentanglement in image sequences
NeurIPS 2022
Gradient-based Hyperparameter Optimization Over Long Horizons
NeurIPS 2021
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
NeurIPS 2020
Self-Supervised Relational Reasoning for Representation Learning
NeurIPS 2020
Learning to Learn By Self-Critique
NeurIPS 2019
Zero-shot Knowledge Transfer via Adversarial Belief Matching
NeurIPS 2019
Moonshine: Distilling with Cheap Convolutions
NeurIPS 2018
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
NeurIPS 2015
Continuous Relaxations for Discrete Hamiltonian Monte Carlo
NeurIPS 2012
The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes
NeurIPS 2012
Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability
NeurIPS 2011
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model
NeurIPS 2010
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
NeurIPS 2010
Continuous Time Particle Filtering for fMRI
NeurIPS 2007
Modelling motion primitives and their timing in biologically executed movements
NeurIPS 2007
Learning Structural Equation Models for fMRI
NeurIPS 2006
Mixture Regression for Covariate Shift
NeurIPS 2006