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ORCIDPiyush Rai
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Publications
- 2021
[c61]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR 2021: 13865-13875- [c57]Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai:
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks. NeurIPS 2021: 15175-15187 - [i40]Sakshi Varshney, Vinay Kumar Verma, Lawrence Carin, Piyush Rai:
Efficient Continual Adaptation for Generative Adversarial Networks. CoRR abs/2103.04032 (2021) - [i39]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR abs/2103.13558 (2021) - 2020
- [c50]Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai:
Calibrating CNNs for Lifelong Learning. NeurIPS 2020 - 2019
- [c40]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. ICML 2019: 4466-4474 - [i21]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. CoRR abs/1905.05738 (2019) - 2018
- [c38]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. AAAI 2018: 4211-4218 - 2017
- [c31]Changwei Hu, Piyush Rai, Lawrence Carin:
Deep Generative Models for Relational Data with Side Information. ICML 2017: 1578-1586 - [i7]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. CoRR abs/1711.05820 (2017) - 2016
- [c27]Changwei Hu, Piyush Rai, Lawrence Carin:
Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. AISTATS 2016: 1124-1132 - [c26]Changwei Hu, Piyush Rai, Lawrence Carin:
Topic-Based Embeddings for Learning from Large Knowledge Graphs. AISTATS 2016: 1133-1141 - [c24]Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin
:
Deep Metric Learning with Data Summarization. ECML/PKDD (1) 2016: 777-794 - [i5]Wenlin Wang, Changyou Chen, Wenqi Wang, Piyush Rai, Lawrence Carin:
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification. CoRR abs/1611.04578 (2016) - 2015
- [c23]Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin:
Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data. AAAI 2015: 2757-2763 - [c22]Piyush Rai, Yingjian Wang, Lawrence Carin:
Leveraging Features and Networks for Probabilistic Tensor Decomposition. AAAI 2015: 2942-2948 - [c21]Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin:
Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision. AAAI 2015: 3203-3209 - [c20]Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin:
Scalable Probabilistic Tensor Factorization for Binary and Count Data. IJCAI 2015: 3770-3776 - [c19]Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin:
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. NIPS 2015: 3222-3230 - [c18]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data. ECML/PKDD (2) 2015: 53-70 - [c17]Changwei Hu, Piyush Rai, Lawrence Carin:
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. UAI 2015: 375-384 - [i4]Changwei Hu, Piyush Rai, Lawrence Carin:
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. CoRR abs/1508.04210 (2015) - [i3]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data. CoRR abs/1508.04211 (2015) - 2014
- [c16]Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin:
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. ICML 2014: 1800-1808
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