Hemanth Saratchandran

According to our database1, Hemanth Saratchandran authored at least 25 papers between 2022 and 2025.

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

Timeline

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Bibliography

2025
Transformers Pretrained on Procedural Data Contain Modular Structures for Algorithmic Reasoning.
CoRR, May, 2025

Compressing Sine-Activated Low-Rank Adapters through Post-Training Quantization.
CoRR, May, 2025

Leaner Transformers: More Heads, Less Depth.
CoRR, May, 2025

Structured Initialization for Vision Transformers.
CoRR, May, 2025

Enhancing Transformers Through Conditioned Embedded Tokens.
CoRR, May, 2025

Always Skip Attention.
CoRR, May, 2025

Efficient Learning with Sine-Activated Low-Rank Matrices.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

RandLoRA: Full rank parameter-efficient fine-tuning of large models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Preconditioners for the Stochastic Training of Neural Fields.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
Rethinking Softmax: Self-Attention with Polynomial Activations.
CoRR, 2024

Sine Activated Low-Rank Matrices for Parameter Efficient Learning.
CoRR, 2024

Preconditioners for the Stochastic Training of Implicit Neural Representations.
CoRR, 2024

Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks.
CoRR, 2024

Architectural Strategies for the optimization of Physics-Informed Neural Networks.
CoRR, 2024

A sampling theory perspective on activations for implicit neural representations.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Weight Conditioning for Smooth Optimization of Neural Networks.
Proceedings of the Computer Vision - ECCV 2024, 2024

Invertible Neural Warp for NeRF.
Proceedings of the Computer Vision - ECCV 2024, 2024

From Activation to Initialization: Scaling Insights for Optimizing Neural Fields.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

D'OH: Decoder-Only Random Hypernetworks for Implicit Neural Representations.
Proceedings of the Computer Vision - ACCV 2024, 2024

2023
On the effectiveness of neural priors in modeling dynamical systems.
CoRR, 2023

On skip connections and normalisation layers in deep optimisation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

How much does Initialization Affect Generalization?
Proceedings of the International Conference on Machine Learning, 2023

Curvature-Aware Training for Coordinate Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
A global analysis of global optimisation.
CoRR, 2022

How You Start Matters for Generalization.
CoRR, 2022


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