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2020 – today
- 2024
[j2]David K. Lim
, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Deeply Learned Generalized Linear Models with Missing Data. J. Comput. Graph. Stat. 33(2): 638-650 (2024)- [c34]Siyuan Shan, Yang Li, Amartya Banerjee, Junier B. Oliva:
Phoneme Hallucinator: One-Shot Voice Conversion via Set Expansion. AAAI 2024: 14910-14918 - [c33]Michael Valancius, Max Lennon, Junier Oliva:
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition. ICML 2024 - [c32]Boqi Chen, Junier Oliva, Marc Niethammer:
A Unified Model for Longitudinal Multi-Modal Multi-View Prediction with Missingness. MICCAI (12) 2024: 410-420 - [i41]Boqi Chen, Junier Oliva, Marc Niethammer:
A Unified Model for Longitudinal Multi-Modal Multi-View Prediction with Missingness. CoRR abs/2403.12211 (2024) - [i40]Yunni Qu, James Wellnitz, Alexander Tropsha, Junier Oliva:
EMOE: Expansive Matching of Experts for Robust Uncertainty Based Rejection. CoRR abs/2406.01825 (2024) - [i39]Ahsan Mahmood, Junier Oliva, Martin Styner:
Localizing Anomalies via Multiscale Score Matching Analysis. CoRR abs/2407.00148 (2024) - [i38]Yang Li, Junier Oliva:
Towards Cost Sensitive Decision Making. CoRR abs/2410.03892 (2024) - [i37]Yang Li, Junier Oliva:
Distribution Guided Active Feature Acquisition. CoRR abs/2410.03915 (2024) - 2023
- [c31]Siyuan Shan, Yang Li, Junier B. Oliva:
NRTSI: Non-Recurrent Time Series Imputation. ICASSP 2023: 1-5 - [c30]Christopher M. Bender, Yifeng Shi, Marc Niethammer, Junier Oliva:
Continuously Parameterized Mixture Models. ICML 2023: 2050-2062 - [i36]Michael Valancius, Max Lennon, Junier Oliva:
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition. CoRR abs/2302.13960 (2023) - [i35]Ahsan Mahmood, Junier Oliva, Martin Styner:
Anomaly Detection via Gumbel Noise Score Matching. CoRR abs/2304.03220 (2023) - [i34]Siyuan Shan, Yang Li, Amartya Banerjee, Junier B. Oliva:
Phoneme Hallucinator: One-shot Voice Conversion via Set Expansion. CoRR abs/2308.06382 (2023) - 2022
- [c29]Siyuan Shan, Vishal Athreya Baskaran, Haidong Yi, Jolene Ranek, Natalie Stanley, Junier B. Oliva:
Transparent single-cell set classification with kernel mean embeddings. BCB 2022: 25:1-25:10 - [c28]Vishal Athreya Baskaran, Jolene Ranek, Siyuan Shan, Natalie Stanley, Junier B. Oliva:
Distribution-based sketching of single-cell samples. BCB 2022: 26:1-26:10 - [c27]Christopher M. Bender, Patrick Emmanuel, Michael K. Reiter, Junier Oliva:
Practical Integration via Separable Bijective Networks. ICLR 2022 - [c26]Avinash Madasu, Junier Oliva, Gedas Bertasius:
Learning to Retrieve Videos by Asking Questions. ACM Multimedia 2022: 356-365 - [c25]Ryan R. Strauss, Junier B. Oliva:
Posterior Matching for Arbitrary Conditioning. NeurIPS 2022 - [i33]Siyuan Shan, Vishal Baskaran, Haidong Yi, Jolene Ranek, Natalie Stanley, Junier Oliva:
Interpretable Single-Cell Set Classification with Kernel Mean Embeddings. CoRR abs/2201.07322 (2022) - [i32]Ryan R. Strauss, Junier B. Oliva:
Any Variational Autoencoder Can Do Arbitrary Conditioning. CoRR abs/2201.12414 (2022) - [i31]Avinash Madasu, Junier Oliva, Gedas Bertasius:
Learning to Retrieve Videos by Asking Questions. CoRR abs/2205.05739 (2022) - [i30]Vishal Athreya Baskaran, Jolene Ranek, Siyuan Shan, Natalie Stanley, Junier B. Oliva:
Distribution-based Sketching of Single-Cell Samples. CoRR abs/2207.00584 (2022) - [i29]David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Deeply-Learned Generalized Linear Models with Missing Data. CoRR abs/2207.08911 (2022) - 2021
- [c24]Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li, Junier Oliva, Shashank Srivastava, Snigdha Chaturvedi:
Adversarial Scrubbing of Demographic Information for Text Classification. EMNLP (1) 2021: 550-562 - [c23]Ahsan Mahmood, Junier Oliva, Martin Andreas Styner:
Multiscale Score Matching for Out-of-Distribution Detection. ICLR 2021 - [c22]Yang Li, Junier Oliva:
Active Feature Acquisition with Generative Surrogate Models. ICML 2021: 6450-6459 - [c21]Yang Li, Junier Oliva:
Partially Observed Exchangeable Modeling. ICML 2021: 6460-6470 - [c20]Ryan R. Strauss, Junier B. Oliva:
Arbitrary Conditional Distributions with Energy. NeurIPS 2021: 752-763 - [i28]David K. Lim, Naim U. Rashid, Junier B. Oliva, Joseph G. Ibrahim:
Handling Non-ignorably Missing Features in Electronic Health Records Data Using Importance-Weighted Autoencoders. CoRR abs/2101.07357 (2021) - [i27]Siyuan Shan, Junier B. Oliva:
NRTSI: Non-Recurrent Time Series Imputation for Irregularly-sampled Data. CoRR abs/2102.03340 (2021) - [i26]Ryan R. Strauss, Junier B. Oliva:
Arbitrary Conditional Distributions with Energy. CoRR abs/2102.04426 (2021) - [i25]Yang Li, Junier B. Oliva:
Partially Observed Exchangeable Modeling. CoRR abs/2102.06083 (2021) - [i24]Yang Li, Siyuan Shan, Qin Liu, Junier B. Oliva:
Towards Robust Active Feature Acquisition. CoRR abs/2107.04163 (2021) - [i23]Somnath Basu Roy Chowdhury, Sayan Ghosh, Yiyuan Li, Junier B. Oliva, Shashank Srivastava, Snigdha Chaturvedi:
Adversarial Scrubbing of Demographic Information for Text Classification. CoRR abs/2109.08613 (2021) - 2020
- [c19]Yang Li, Tianxiang Gao, Junier Oliva:
A Forest from the Trees: Generation through Neighborhoods. AAAI 2020: 4755-4762 - [c18]Yifeng Shi, Junier Oliva, Marc Niethammer:
Deep Message Passing on Sets. AAAI 2020: 5750-5757 - [c17]Christopher M. Bender, Kevin O'Connor, Yang Li, Juan Jose Garcia, Junier Oliva, Manzil Zaheer:
Exchangeable Generative Models with Flow Scans. AAAI 2020: 10053-10060 - [c16]Christopher M. Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier Oliva:
Defense Through Diverse Directions. ICML 2020: 756-766 - [c15]Yang Li, Shoaib Akbar, Junier Oliva:
ACFlow: Flow Models for Arbitrary Conditional Likelihoods. ICML 2020: 5831-5841 - [c14]Yang Li, Haidong Yi, Christopher M. Bender, Siyuan Shan, Junier B. Oliva:
Exchangeable Neural ODE for Set Modeling. NeurIPS 2020 - [c13]Siyuan Shan, Yang Li, Junier B. Oliva:
Meta-Neighborhoods. NeurIPS 2020 - [i22]Christopher M. Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier B. Oliva:
Defense Through Diverse Directions. CoRR abs/2003.10602 (2020) - [i21]Yifeng Shi, Christopher M. Bender, Junier B. Oliva, Marc Niethammer:
Deep Goal-Oriented Clustering. CoRR abs/2006.04259 (2020) - [i20]Yang Li, Junier B. Oliva:
Dynamic Feature Acquisition with Arbitrary Conditional Flows. CoRR abs/2006.07701 (2020) - [i19]Yang Li, Haidong Yi, Christopher M. Bender, Siyuan Shan, Junier B. Oliva:
Exchangeable Neural ODE for Set Modeling. CoRR abs/2008.02676 (2020) - [i18]Yang Li, Junier B. Oliva:
Active Feature Acquisition with Generative Surrogate Models. CoRR abs/2010.02433 (2020) - [i17]Ahsan Mahmood, Junier Oliva, Martin Styner:
Multiscale Score Matching for Out-of-Distribution Detection. CoRR abs/2010.13132 (2020)
2010 – 2019
- 2019
- [b1]Junier B. Oliva:
Distribution and Histogram (DisH) Learning. Carnegie Mellon University, USA, 2019 - [j1]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. J. Artif. Intell. Res. 66: 151-196 (2019) - [c12]Eunbyung Park, Junier B. Oliva:
Meta-Curvature. NeurIPS 2019: 3309-3319 - [i16]Yang Li, Tianxiang Gao, Junier Oliva:
A Forest from the Trees: Generation through Neighborhoods. CoRR abs/1902.01435 (2019) - [i15]Christopher M. Bender, Juan Jose Garcia, Kevin O'Connor, Junier Oliva:
Permutation Invariant Likelihoods and Equivariant Transformations. CoRR abs/1902.01967 (2019) - [i14]Eunbyung Park, Junier B. Oliva:
Meta-Curvature. CoRR abs/1902.03356 (2019) - [i13]Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev:
MolecularRNN: Generating realistic molecular graphs with optimized properties. CoRR abs/1905.13372 (2019) - [i12]Yang Li, Shoaib Akbar, Junier B. Oliva:
Flow Models for Arbitrary Conditional Likelihoods. CoRR abs/1909.06319 (2019) - [i11]Siyuan Shan, Junier Oliva:
Meta-Neighborhoods. CoRR abs/1909.09140 (2019) - [i10]Yifeng Shi, Junier Oliva, Marc Niethammer:
Deep Message Passing on Sets. CoRR abs/1909.09877 (2019) - 2018
- [c11]Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider:
Transformation Autoregressive Networks. ICML 2018: 3895-3904 - 2017
- [c10]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
The Statistical Recurrent Unit. ICML 2017: 2671-2680 - [i9]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
The Statistical Recurrent Unit. CoRR abs/1703.00381 (2017) - [i8]Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider:
Recurrent Estimation of Distributions. CoRR abs/1705.10750 (2017) - [i7]Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne C. Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos:
Estimating Cosmological Parameters from the Dark Matter Distribution. CoRR abs/1711.02033 (2017) - 2016
- [c9]Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Linear-Time Learning on Distributions with Approximate Kernel Embeddings. AAAI 2016: 2073-2079 - [c8]Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Bayesian Nonparametric Kernel-Learning. AISTATS 2016: 1078-1086 - [c7]Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos:
Estimating Cosmological Parameters from the Dark Matter Distribution. ICML 2016: 2407-2416 - [c6]Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI 2016: 2146-2152 - [c5]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations. NIPS 2016: 992-1000 - [i6]Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos:
Multi-fidelity Gaussian Process Bandit Optimisation. CoRR abs/1603.06288 (2016) - 2015
- [c4]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider:
Fast Function to Function Regression. AISTATS 2015 - [i5]Danica J. Sutherland, Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Linear-time Learning on Distributions with Approximate Kernel Embeddings. CoRR abs/1509.07553 (2015) - [i4]Junier B. Oliva, Danica J. Sutherland, Barnabás Póczos, Jeff G. Schneider:
Deep Mean Maps. CoRR abs/1511.04150 (2015) - 2014
- [c3]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Fast Distribution To Real Regression. AISTATS 2014: 706-714 - [c2]Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng:
FuSSO: Functional Shrinkage and Selection Operator. AISTATS 2014: 715-723 - [i3]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider:
Fast Function to Function Regression. CoRR abs/1410.7414 (2014) - 2013
- [c1]Junier B. Oliva, Barnabás Póczos, Jeff G. Schneider:
Distribution to Distribution Regression. ICML (3) 2013: 1049-1057 - [i2]Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng:
FuSSO: Functional Shrinkage and Selection Operator. CoRR abs/1311.2234 (2013) - [i1]Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing:
Fast Distribution To Real Regression. CoRR abs/1311.2236 (2013)
Coauthor Index
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last updated on 2024-11-14 20:55 CET by the dblp team
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