2024
Pathologies of Predictive Diversity in Deep Ensembles.
Trans. Mach. Learn. Res., 2024
Theoretical Limitations of Ensembles in the Age of Overparameterization.
CoRR, 2024
LoRA Learns Less and Forgets Less.
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CoRR, 2024
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Approximation-Aware Bayesian Optimization.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Estimating the Hallucination Rate of Generative AI.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
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.
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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.
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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.
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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.
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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.
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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.
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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