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Ramakrishna Vedantam
Ramakrishna Vedantam
Research Scientist, Facebook AI Research
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Vuosi
Grad-CAM: Why did you say that?
RR Selvaraju, A Das, R Vedantam, M Cogswell, D Parikh, D Batra
IEEE International Conference on Computer Vision (ICCV), 2017, 2016
13591*2016
CIDEr: Consensus-based Image Description Evaluation
R Vedantam, CL Zitnick, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, 2014
32532014
Microsoft coco captions: Data collection and evaluation server
X Chen, H Fang, TY Lin, R Vedantam, S Gupta, P Dollár, CL Zitnick
arXiv preprint arXiv:1504.00325, 2015
16752015
Context-aware captions from context-agnostic supervision
R Vedantam, S Bengio, K Murphy, D Parikh, G Chechik
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2017
1422017
Counting Everyday Objects in Everyday Scenes
P Chattopadhyay, R Vedantam, RS Ramprasaath, D Batra, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2016
1332016
Generative Models of Visually Grounded Imagination
R Vedantam, I Fischer, J Huang, K Murphy
International Conference on Learning Representations (ICLR), 2018, 2018
1182018
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes
S Kottur, R Vedantam, JMF Moura, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, 2015
1132015
Adopting abstract images for semantic scene understanding
CL Zitnick, R Vedantam, D Parikh
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
1002014
Learning Common Sense Through Visual Abstraction
R Vedantam, X Lin, T Batra, CL Zitnick, D Parikh
IEEE International Conference on Computer Vision (ICCV), 2015, 2015
922015
Probabilistic neural symbolic models for interpretable visual question answering
R Vedantam, K Desai, S Lee, M Rohrbach, D Batra, D Parikh
International Conference on Machine Learning, 6428-6437, 2019
672019
Sound-word2vec: Learning word representations grounded in sounds
AK Vijayakumar, R Vedantam, D Parikh
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017, 2017
282017
Learning optimal representations with the decodable information bottleneck
Y Dubois, D Kiela, DJ Schwab, R Vedantam
Advances in Neural Information Processing Systems 33, 18674-18690, 2020
252020
Curi: A benchmark for productive concept learning under uncertainty
R Vedantam, A Szlam, M Nickel, A Morcos, BM Lake
International Conference on Machine Learning, 10519-10529, 2021
182021
An empirical investigation of domain generalization with empirical risk minimizers
R Vedantam, D Lopez-Paz, DJ Schwab
Advances in Neural Information Processing Systems 34, 28131-28143, 2021
152021
Coat: Measuring object compositionality in emergent representations
S Xie, AS Morcos, SC Zhu, R Vedantam
International Conference on Machine Learning, 24388-24413, 2022
32022
DS-VIC: Unsupervised Discovery of Decision States for Transfer in RL
N Modhe, P Chattopadhyay, M Sharma, A Das, D Parikh, D Batra, ...
3*
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