Suraj Srinivas

According to our database1, Suraj Srinivas authored at least 34 papers between 2014 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Generalized Group Data Attribution.
CoRR, 2024

How much can we forget about Data Contamination?
CoRR, 2024

All Roads Lead to Rome? Exploring Representational Similarities Between Latent Spaces of Generative Image Models.
CoRR, 2024

Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE).
CoRR, 2024

2023
Certifying LLM Safety against Adversarial Prompting.
CoRR, 2023

Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability.
CoRR, 2023

Efficient Estimation of the Local Robustness of Machine Learning Models.
CoRR, 2023

Consistent Explanations in the Face of Model Indeterminacy via Ensembling.
CoRR, 2023

Word-Level Explanations for Analyzing Bias in Text-to-Image Models.
CoRR, 2023

On Minimizing the Impact of Dataset Shifts on Actionable Explanations.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Flatten the Curve: Efficiently Training Low-Curvature Neural Networks.
CoRR, 2022

Efficient Training of Low-Curvature Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Data-Efficient Structured Pruning via Submodular Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Cyclical Pruning for Sparse Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Gradient Alignment in Deep Neural Networks.
CoRR, 2020

2019
Full-Jacobian Representation of Neural Networks.
CoRR, 2019

Full-Gradient Representation for Neural Network Visualization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Estimating Confidence for Deep Neural Networks through Density modeling.
Proceedings of the 2018 International Conference on Signal Processing and Communications (SPCOM), 2018

Knowledge Transfer with Jacobian Matching.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Confidence estimation in Deep Neural networks via density modelling.
CoRR, 2017

Training Sparse Neural Networks.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

An Introduction to Deep Convolutional Neural Nets for Computer Vision.
Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017

2016
Generalized Dropout.
CoRR, 2016

Compensating for large in-plane rotations in natural images.
Proceedings of the Tenth Indian Conference on Computer Vision, 2016

Learning Neural Network Architectures using Backpropagation.
Proceedings of the British Machine Vision Conference 2016, 2016

2015
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision.
Frontiers Robotics AI, 2015

Learning the Architecture of Deep Neural Networks.
CoRR, 2015

Data-free Parameter Pruning for Deep Neural Networks.
Proceedings of the British Machine Vision Conference 2015, 2015

2014
Universal Gestural Remote: A Conceptual Framework for a Human-Device Interface.
Aust. J. Intell. Inf. Process. Syst., 2014

Controlled blurring for improving image reconstruction quality in flutter-shutter acquisition.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014


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