Junier B. Oliva

According to our database, Junier B. Oliva authored at least 57 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deeply Learned Generalized Linear Models with Missing Data.

David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim

J. Comput. Graph. Stat., 2024

Anomaly detection via Gumbel Noise Score Matching.

Ahsan Mahmood, Junier Oliva, Martin Andreas Styner

Frontiers Artif. Intell., 2024

Dynamic Information Sub-Selection for Decision Support.

Hung-Tien Huang, Maxwell Lennon, Shreyas Bhat Brahmavar, Sean Sylvia, Junier B. Oliva

CoRR, 2024

Distribution Guided Active Feature Acquisition.

Yang Li, Junier Oliva

CoRR, 2024

Towards Cost Sensitive Decision Making.

Yang Li, Junier Oliva

CoRR, 2024

Localizing Anomalies via Multiscale Score Matching Analysis.

Ahsan Mahmood, Junier Oliva, Martin Styner

CoRR, 2024

EMOE: Expansive Matching of Experts for Robust Uncertainty Based Rejection.

Yunni Qu, James Wellnitz, Alexander Tropsha, Junier Oliva

CoRR, 2024

A Unified Model for Longitudinal Multi-Modal Multi-View Prediction with Missingness.

Boqi Chen, Junier Oliva, Marc Niethammer

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition.

Michael Valancius, Max Lennon, Junier Oliva

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Phoneme Hallucinator: One-Shot Voice Conversion via Set Expansion.

Siyuan Shan, Yang Li, Amartya Banerjee, Junier B. Oliva

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Continuously Parameterized Mixture Models.

Christopher M. Bender, Yifeng Shi, Marc Niethammer, Junier Oliva

Proceedings of the International Conference on Machine Learning, 2023

NRTSI: Non-Recurrent Time Series Imputation.

Siyuan Shan, Yang Li, Junier B. Oliva

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Any Variational Autoencoder Can Do Arbitrary Conditioning.

Ryan R. Strauss, Junier B. Oliva

CoRR, 2022

Interpretable Single-Cell Set Classification with Kernel Mean Embeddings.

Siyuan Shan, Vishal Baskaran, Haidong Yi, Jolene Ranek, Natalie Stanley, Junier Oliva

CoRR, 2022

Posterior Matching for Arbitrary Conditioning.

Ryan R. Strauss, Junier B. Oliva

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning to Retrieve Videos by Asking Questions.

Avinash Madasu, Junier Oliva, Gedas Bertasius

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Practical Integration via Separable Bijective Networks.

Christopher M. Bender, Patrick Emmanuel, Michael K. Reiter, Junier Oliva

Proceedings of the Tenth International Conference on Learning Representations, 2022

Transparent single-cell set classification with kernel mean embeddings.

Siyuan Shan, Vishal Athreya Baskaran, Haidong Yi, Jolene Ranek, Natalie Stanley, Junier B. Oliva

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

Distribution-based sketching of single-cell samples.

Vishal Athreya Baskaran, Jolene Ranek, Siyuan Shan, Natalie Stanley, Junier B. Oliva

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

2021

Towards Robust Active Feature Acquisition.

Yang Li, Siyuan Shan, Qin Liu, Junier B. Oliva

CoRR, 2021

NRTSI: Non-Recurrent Time Series Imputation for Irregularly-sampled Data.

Siyuan Shan, Junier B. Oliva

CoRR, 2021

Handling Non-ignorably Missing Features in Electronic Health Records Data Using Importance-Weighted Autoencoders.

David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim

CoRR, 2021

Arbitrary Conditional Distributions with Energy.

Ryan R. Strauss, Junier B. Oliva

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Partially Observed Exchangeable Modeling.

Yang Li, Junier Oliva

Proceedings of the 38th International Conference on Machine Learning, 2021

Active Feature Acquisition with Generative Surrogate Models.

Yang Li, Junier Oliva

Proceedings of the 38th International Conference on Machine Learning, 2021

Multiscale Score Matching for Out-of-Distribution Detection.

Ahsan Mahmood, Junier Oliva, Martin Andreas Styner

Proceedings of the 9th International Conference on Learning Representations, 2021

Adversarial Scrubbing of Demographic Information for Text Classification.

Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li, Junier Oliva, Shashank Srivastava, Snigdha Chaturvedi

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Dynamic Feature Acquisition with Arbitrary Conditional Flows.

Yang Li, Junier B. Oliva

CoRR, 2020

Deep Goal-Oriented Clustering.

Yifeng Shi, Christopher M. Bender, Junier B. Oliva, Marc Niethammer

CoRR, 2020

Meta-Neighborhoods.

Siyuan Shan, Yang Li, Junier B. Oliva

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Exchangeable Neural ODE for Set Modeling.

Yang Li, Haidong Yi, Christopher M. Bender, Siyuan Shan, Junier B. Oliva

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

ACFlow: Flow Models for Arbitrary Conditional Likelihoods.

Yang Li, Shoaib Akbar, Junier Oliva

Proceedings of the 37th International Conference on Machine Learning, 2020

Defense Through Diverse Directions.

Christopher M. Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier Oliva

Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Message Passing on Sets.

Yifeng Shi, Junier Oliva, Marc Niethammer

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

A Forest from the Trees: Generation through Neighborhoods.

Yang Li, Tianxiang Gao, Junier Oliva

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Exchangeable Generative Models with Flow Scans.

Christopher M. Bender, Kevin O'Connor, Yang Li, Juan Jose Garcia, Junier Oliva, Manzil Zaheer

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Distribution and Histogram (DisH) Learning.

Junier B. Oliva

PhD thesis, 2019

Multi-fidelity Gaussian Process Bandit Optimisation.

Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

J. Artif. Intell. Res., 2019

Meta-Neighborhoods.

Siyuan Shan, Junier Oliva

CoRR, 2019

Flow Models for Arbitrary Conditional Likelihoods.

Yang Li, Shoaib Akbar, Junier B. Oliva

CoRR, 2019

MolecularRNN: Generating realistic molecular graphs with optimized properties.

Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev

CoRR, 2019

Permutation Invariant Likelihoods and Equivariant Transformations.

Christopher M. Bender, Juan Jose Garcia, Kevin O'Connor, Junier Oliva

CoRR, 2019

Meta-Curvature.

Eunbyung Park, Junier B. Oliva

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Transformation Autoregressive Networks.

Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Recurrent Estimation of Distributions.

Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider

CoRR, 2017

The Statistical Recurrent Unit.

Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations.

Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems.

Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Estimating Cosmological Parameters from the Dark Matter Distribution.

Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos

Proceedings of the 33nd International Conference on Machine Learning, 2016

Bayesian Nonparametric Kernel-Learning.

Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Linear-Time Learning on Distributions with Approximate Kernel Embeddings.

Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Deep Mean Maps.

Junier B. Oliva, Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider

CoRR, 2015

Fast Function to Function Regression.

Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Fast Function to Function Regression.

Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider

CoRR, 2014

FuSSO: Functional Shrinkage and Selection Operator.

Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Fast Distribution To Real Regression.

Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Distribution to Distribution Regression.

Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider

Proceedings of the 30th International Conference on Machine Learning, 2013