John P. Cunningham

Affiliations:
  • Columbia University, Department of Statistics, New York, NY, USA
  • Washington University in St. Louis, Department of Electrical & Systems Engineering, MO, USA
  • University of Cambridge, Department of Engineering, UK
  • Stanford University, Department of Electrical Engineering, CA, USA (PhD 2009)


According to our database1, John P. Cunningham authored at least 82 papers between 2006 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Pathologies of Predictive Diversity in Deep Ensembles.
CoRR, 2023

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
On the Normalizing Constant of the Continuous Categorical Distribution.
CoRR, 2022

Variational Nearest Neighbor Gaussian Processes.
CoRR, 2022

Posterior and Computational Uncertainty in Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Ensembles Work, But Are They Necessary?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Variational nearest neighbor Gaussian process.
Proceedings of the International Conference on Machine Learning, 2022

Preconditioning for Scalable Gaussian Process Hyperparameter Optimization.
Proceedings of the International Conference on Machine Learning, 2022

Scaling Structured Inference with Randomization.
Proceedings of the International Conference on Machine Learning, 2022

Denoising Deep Generative Models.
Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

2021
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.
PLoS Comput. Biol., 2021

Designing clinically translatable artificial intelligence systems for high-dimensional medical imaging.
Nat. Mach. Intell., 2021

A general linear-time inference method for Gaussian Processes on one dimension.
J. Mach. Learn. Res., 2021

Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning.
CoRR, 2021

Simulating time to event prediction with spatiotemporal echocardiography deep learning.
CoRR, 2021

Medical Imaging and Machine Learning.
CoRR, 2021

Hierarchical Inducing Point Gaussian Process for Inter-domain Observations.
CoRR, 2021

Predicting post-operative right ventricular failure using video-based deep learning.
CoRR, 2021

Learning sparse log-ratios for high-throughput sequencing data.
Bioinform., 2021

Posterior Collapse and Latent Variable Non-identifiability.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rectangular Flows for Manifold Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bias-Free Scalable Gaussian Processes via Randomized Truncations.
Proceedings of the 38th International Conference on Machine Learning, 2021

Hierarchical Inducing Point Gaussian Process for Inter-domian Observations.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data.
J. Mach. Learn. Res., 2020

General linear-time inference for Gaussian Processes on one dimension.
CoRR, 2020

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The continuous categorical: a novel simplex-valued exponential family.
Proceedings of the 37th International Conference on Machine Learning, 2020

Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning.
Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

2019
Approximating exponential family models (not single distributions) with a two-network architecture.
CoRR, 2019

Deep Random Splines for Point Process Intensity Estimation of Neural Population Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The continuous Bernoulli: fixing a pervasive error in variational autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Paraphrase Generation with Latent Bag of Words.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Random Splines for Point Process Intensity Estimation.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Calibrating Deep Convolutional Gaussian Processes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Probabilistic Model of Cardiac Physiology and Electrocardiograms.
CoRR, 2018

A Novel Variational Family for Hidden Nonlinear Markov Models.
CoRR, 2018

Bayesian estimation for large scale multivariate Ornstein-Uhlenbeck model of brain connectivity.
CoRR, 2018

Reparameterizing the Birkhoff Polytope for Variational Permutation Inference.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays.
PLoS Comput. Biol., 2017

Sparse probit linear mixed model.
Mach. Learn., 2017

Maximum Entropy Flow Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Annular Augmentation Sampling.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1.
PLoS Comput. Biol., 2016

Neuroprosthetic Decoder Training as Imitation Learning.
PLoS Comput. Biol., 2016

Bayesian Learning of Kernel Embeddings.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Elliptical Slice Sampling with Expectation Propagation.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Automated scalable segmentation of neurons from multispectral images.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Linear dynamical neural population models through nonlinear embeddings.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Preconditioning Kernel Matrices.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Slice Sampling on Hamiltonian Trajectories.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Encoder-Decoder Optimization for Brain-Computer Interfaces.
PLoS Comput. Biol., 2015

Scaling Multidimensional Inference for Structured Gaussian Processes.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Linear dimensionality reduction: survey, insights, and generalizations.
J. Mach. Learn. Res., 2015

Sparse Estimation in a Correlated Probit Model.
CoRR, 2015

Psychophysical Detection Testing with Bayesian Active Learning.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Bayesian Active Model Selection with an Application to Automated Audiometry.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

High-dimensional neural spike train analysis with generalized count linear dynamical systems.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Fast Kernel Learning for Multidimensional Pattern Extrapolation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Clustered factor analysis of multineuronal spike data.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Bayesian Optimization with Inequality Constraints.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
GPatt: Fast Multidimensional Pattern Extrapolation with Gaussian Processes.
CoRR, 2013

Scaling Multidimensional Gaussian Processes using Projected Additive Approximations.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Gaussian Processes for time-marked time-series data.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

An L 1-regularized logistic model for detecting short-term neuronal interactions.
J. Comput. Neurosci., 2012

A brain machine interface control algorithm designed from a feedback control perspective.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2011
Dynamical segmentation of single trials from population neural data.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Empirical models of spiking in neural populations.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2009
Methods for estimating neural firing rates, and their application to brain-machine interfaces.
Neural Networks, 2009

Influence of heart rate on the BOLD signal: The cardiac response function.
NeuroImage, 2009

Workshop summary: Numerical mathematics in machine learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Fast Gaussian process methods for point process intensity estimation.
Proceedings of the Machine Learning, 2008

2007
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

2006
Increasing the Performance of Cortically-Controlled Prostheses.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

Optimal Target Placement for Neural Communication Prostheses.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006


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