Jason Ramapuram

Orcid: 0000-0001-9717-1188

According to our database1, Jason Ramapuram authored at least 25 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

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Bibliography

2024
Theory, Analysis, and Best Practices for Sigmoid Self-Attention.
CoRR, 2024

Poly-View Contrastive Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Bootstrap Your Own Variance.
CoRR, 2023

How to Scale Your EMA.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stabilizing Transformer Training by Preventing Attention Entropy Collapse.
Proceedings of the International Conference on Machine Learning, 2023

DUET: 2D Structured and Approximately Equivariant Representations.
Proceedings of the International Conference on Machine Learning, 2023

The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning.
Proceedings of the International Conference on Machine Learning, 2023

2022
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer.
CoRR, 2022

Position Prediction as an Effective Pretraining Strategy.
Proceedings of the International Conference on Machine Learning, 2022

2021
Finding signals in the void: Improving deep latent variable generative models via supervisory signals present within data.
PhD thesis, 2021

Stochastic Contrastive Learning.
CoRR, 2021

Evaluating the fairness of fine-tuning strategies in self-supervised learning.
CoRR, 2021

Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?
CoRR, 2021

Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory.
Proceedings of the 9th International Conference on Learning Representations, 2021

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Challenges of Adversarial Image Augmentations.
Proceedings of the I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 2021

2020
Lifelong generative modeling.
Neurocomputing, 2020

Self-Supervised MultiModal Versatile Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improving Discrete Latent Representations With Differentiable Approximation Bridges.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
Differentiable Approximation Bridges For Training Networks Containing Non-Differentiable Functions.
CoRR, 2019

Variational Saccading: Efficient Inference for Large Resolution Images.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018
Variational Saccading: Efficient Inference for Large Resolution Images.
CoRR, 2018

Continual Classification Learning Using Generative Models.
CoRR, 2018

Large-Scale Nonlinear Variable Selection via Kernel Random Features.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

A New Benchmark and Progress Toward Improved Weakly Supervised Learning.
Proceedings of the British Machine Vision Conference 2018, 2018


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