Ramakrishna Vedantam

According to our database1, Ramakrishna Vedantam authored at least 27 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Embarrassingly Simple Dataset Distillation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Embarassingly Simple Dataset Distillation.
CoRR, 2023

Understanding the detrimental class-level effects of data augmentation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hyperbolic Image-text Representations.
Proceedings of the International Conference on Machine Learning, 2023

Don't forget the nullspace! Nullspace occupancy as a mechanism for out of distribution failure.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Improving Selective Visual Question Answering by Learning from Your Peers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
COAT: Measuring Object Compositionality in Emergent Representations.
Proceedings of the International Conference on Machine Learning, 2022

2021
An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CURI: A Benchmark for Productive Concept Learning Under Uncertainty.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization.
Int. J. Comput. Vis., 2020

Learning Optimal Representations with the Decodable Information Bottleneck.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Unsupervised Discovery of Decision States for Transfer in Reinforcement Learning.
CoRR, 2019

Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Generative Models of Visually Grounded Imagination.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Sound-Word2Vec: Learning Word Representations Grounded in Sounds.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Context-Aware Captions from Context-Agnostic Supervision.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Counting Everyday Objects in Everyday Scenes.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Adopting Abstract Images for Semantic Scene Understanding.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Grad-CAM: Why did you say that?
CoRR, 2016

Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization.
CoRR, 2016

VisualWord2Vec (Vis-W2V): Learning Visually Grounded Word Embeddings Using Abstract Scenes.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes.
CoRR, 2015

Microsoft COCO Captions: Data Collection and Evaluation Server.
CoRR, 2015

Learning Common Sense through Visual Abstraction.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

CIDEr: Consensus-based image description evaluation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Collecting Image Description Datasets using Crowdsourcing.
CoRR, 2014


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