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ORCIDRamakrishna Vedantam
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2020 – today
- 2024
[c19]Yunzhen Feng, Shanmukha Ramakrishna Vedantam, Julia Kempe:
Embarrassingly Simple Dataset Distillation. ICLR 2024- [i18]Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the Detrimental Class-level Effects of Data Augmentation. CoRR abs/2401.01764 (2024) - 2023
- [c18]Corentin Dancette, Spencer Whitehead, Rishabh Maheshwary, Ramakrishna Vedantam, Stefan Scherer, Xinlei Chen, Matthieu Cord, Marcus Rohrbach:
Improving Selective Visual Question Answering by Learning from Your Peers. CVPR 2023: 24049-24059 - [c17]Daksh Idnani, Vivek Madan, Naman Goyal, David J. Schwab, Ramakrishna Vedantam:
Don't forget the nullspace! Nullspace occupancy as a mechanism for out of distribution failure. ICLR 2023 - [c16]Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Shanmukha Ramakrishna Vedantam:
Hyperbolic Image-text Representations. ICML 2023: 7694-7731 - [c15]Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson:
Understanding the detrimental class-level effects of data augmentation. NeurIPS 2023 - [i17]Karan Desai, Maximilian Nickel
, Tanmay Rajpurohit, Justin Johnson, Ramakrishna Vedantam:
Hyperbolic Image-Text Representations. CoRR abs/2304.09172 (2023) - [i16]Corentin Dancette, Spencer Whitehead, Rishabh Maheshwary, Ramakrishna Vedantam, Stefan Scherer, Xinlei Chen, Matthieu Cord, Marcus Rohrbach:
Improving Selective Visual Question Answering by Learning from Your Peers. CoRR abs/2306.08751 (2023) - [i15]Yunzhen Feng, Ramakrishna Vedantam, Julia Kempe:
Embarassingly Simple Dataset Distillation. CoRR abs/2311.07025 (2023) - 2022
- [c14]Sirui Xie, Ari S. Morcos, Song-Chun Zhu, Ramakrishna Vedantam:
COAT: Measuring Object Compositionality in Emergent Representations. ICML 2022: 24388-24413 - 2021
- [c13]Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake:
CURI: A Benchmark for Productive Concept Learning Under Uncertainty. ICML 2021: 10519-10529 - [c12]Ramakrishna Vedantam, David Lopez-Paz, David J. Schwab:
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers. NeurIPS 2021: 28131-28143 - 2020
- [j2]Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra:
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. Int. J. Comput. Vis. 128(2): 336-359 (2020) - [c11]Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam:
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL. IJCAI 2020: 2022-2028 - [c10]Yann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam:
Learning Optimal Representations with the Decodable Information Bottleneck. NeurIPS 2020 - [i14]Yann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam:
Learning Optimal Representations with the Decodable Information Bottleneck. CoRR abs/2009.12789 (2020) - [i13]Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake:
CURI: A Benchmark for Productive Concept Learning Under Uncertainty. CoRR abs/2010.02855 (2020)
2010 – 2019
- 2019
- [c9]Ramakrishna Vedantam, Karan Desai, Stefan Lee, Marcus Rohrbach, Dhruv Batra, Devi Parikh:
Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering. ICML 2019: 6428-6437 - [i12]Ramakrishna Vedantam, Karan Desai, Stefan Lee, Marcus Rohrbach, Dhruv Batra, Devi Parikh:
Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering. CoRR abs/1902.07864 (2019) - [i11]Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam:
Unsupervised Discovery of Decision States for Transfer in Reinforcement Learning. CoRR abs/1907.10580 (2019) - 2018
- [c8]Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy:
Generative Models of Visually Grounded Imagination. ICLR (Poster) 2018 - 2017
- [c7]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-Aware Captions from Context-Agnostic Supervision. CVPR 2017: 1070-1079 - [c6]Prithvijit Chattopadhyay, Ramakrishna Vedantam, Ramprasaath R. Selvaraju, Dhruv Batra, Devi Parikh:
Counting Everyday Objects in Everyday Scenes. CVPR 2017: 4428-4437 - [c5]Ashwin K. Vijayakumar, Ramakrishna Vedantam, Devi Parikh:
Sound-Word2Vec: Learning Word Representations Grounded in Sounds. EMNLP 2017: 920-925 - [c4]Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra:
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. ICCV 2017: 618-626 - [i10]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-aware Captions from Context-agnostic Supervision. CoRR abs/1701.02870 (2017) - [i9]Ashwin K. Vijayakumar, Ramakrishna Vedantam, Devi Parikh:
Sound-Word2Vec: Learning Word Representations Grounded in Sounds. CoRR abs/1703.01720 (2017) - [i8]Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy:
Generative Models of Visually Grounded Imagination. CoRR abs/1705.10762 (2017) - 2016
- [j1]C. Lawrence Zitnick, Ramakrishna Vedantam, Devi Parikh:
Adopting Abstract Images for Semantic Scene Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 38(4): 627-638 (2016) - [c3]Satwik Kottur, Ramakrishna Vedantam, José M. F. Moura, Devi Parikh:
VisualWord2Vec (Vis-W2V): Learning Visually Grounded Word Embeddings Using Abstract Scenes. CVPR 2016: 4985-4994 - [i7]Prithvijit Chattopadhyay, Ramakrishna Vedantam, Ramprasaath R. Selvaraju, Dhruv Batra, Devi Parikh:
Counting Everyday Objects in Everyday Scenes. CoRR abs/1604.03505 (2016) - [i6]Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra:
Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization. CoRR abs/1610.02391 (2016) - [i5]Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra:
Grad-CAM: Why did you say that? CoRR abs/1611.07450 (2016) - 2015
- [c2]Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh:
CIDEr: Consensus-based image description evaluation. CVPR 2015: 4566-4575 - [c1]Ramakrishna Vedantam, Xiao Lin, Tanmay Batra, C. Lawrence Zitnick, Devi Parikh:
Learning Common Sense through Visual Abstraction. ICCV 2015: 2542-2550 - [i4]Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, C. Lawrence Zitnick:
Microsoft COCO Captions: Data Collection and Evaluation Server. CoRR abs/1504.00325 (2015) - [i3]Satwik Kottur, Ramakrishna Vedantam, José M. F. Moura, Devi Parikh:
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes. CoRR abs/1511.07067 (2015) - 2014
- [i2]Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh:
Collecting Image Description Datasets using Crowdsourcing. CoRR abs/1411.3041 (2014) - [i1]Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh:
CIDEr: Consensus-based Image Description Evaluation. CoRR abs/1411.5726 (2014)
Coauthor Index
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