John P. Cunningham
30 papers · 2007–2024 · 2 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+9 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (58) π Conference Polyglot Β· Bronze π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π
Conference Loyalist
(27)
π¬
Deep Specialist
(10)
π
Keyword Champion
π
Renaissance Researcher
(8)
π
Trend Setter
β
The Questioner
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(167)
π
Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(27)
Artificial Intelligence
(14)
Core Methods
(14)
Optimization & Theory
(14)
Bayesian & Probabilistic Β· Machine Learning
(13)
Deep Learning
(12)
Bayesian & Probabilistic Β· Artificial Intelligence
(11)
Learning Types
(10)
Interdisciplinary
(9)
Science
(9)
Models
(8)
Healthcare & Medicine
(6)
Research
(4)
Data Science & Analytics
(3)
Architectures
(3)
Keywords
variational inference
(12)
gaussian process
(10)
neural population
(6)
bayesian inference
(4)
variational autoencoder
(4)
dimensionality reduction
(3)
point process
(3)
uncertainty quantification
(3)
latent variable model
(3)
linear dynamical system
(3)
latent variable
(2)
model selection
(2)
factor analysis
(2)
firing rate
(2)
generalized linear model
(2)
posterior approximation
(2)
calcium imaging
(2)
generative model
(2)
hierarchical model
(2)
expectation maximization
(2)
Papers
Approximation-Aware Bayesian Optimization
NeurIPS 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
NeurIPS 2024
Estimating the Hallucination Rate of Generative AI
NeurIPS 2024
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
NeurIPS 2023
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome
NeurIPS 2022
Deep Ensembles Work, But Are They Necessary?
NeurIPS 2022
Posterior and Computational Uncertainty in Gaussian Processes
NeurIPS 2022
A general linear-time inference method for Gaussian Processes on one dimension
JMLR 2021
Posterior Collapse and Latent Variable Non-identifiability
NeurIPS 2021
Rectangular Flows for Manifold Learning
NeurIPS 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
NeurIPS 2021
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
NeurIPS 2020
Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data
JMLR 2020
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax
NeurIPS 2020
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations
NeurIPS 2020
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos
NeurIPS 2019
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data
NeurIPS 2019
Paraphrase Generation with Latent Bag of Words
NeurIPS 2019
The continuous Bernoulli: fixing a pervasive error in variational autoencoders
NeurIPS 2019
Automated scalable segmentation of neurons from multispectral images
NeurIPS 2016
Linear dynamical neural population models through nonlinear embeddings
NeurIPS 2016
Bayesian Active Model Selection with an Application to Automated Audiometry
NeurIPS 2015
High-dimensional neural spike train analysis with generalized count linear dynamical systems
NeurIPS 2015
Linear Dimensionality Reduction: Survey, Insights, and Generalizations
JMLR 2015
Clustered factor analysis of multineuronal spike data
NeurIPS 2014
Fast Kernel Learning for Multidimensional Pattern Extrapolation
NeurIPS 2014
Dynamical segmentation of single trials from population neural data
NeurIPS 2011
Empirical models of spiking in neural populations
NeurIPS 2011
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity
NeurIPS 2008
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
NeurIPS 2007