Arka Daw

Orcid: 0009-0006-3319-1271

According to our database1, Arka Daw authored at least 18 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Motion Enhanced Multi-Level Tracker (MEMTrack): A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments.
Adv. Intell. Syst., April, 2024

Physics-informed Machine Learning with Uncertainty Quantification.
PhD thesis, 2024

Hiding-in-Plain-Sight (HiPS) Attack on CLIP for Targetted Object Removal from Images.
CoRR, 2024

A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations.
CoRR, 2024

What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits.
CoRR, 2024

VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images.
CoRR, 2024

Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images.
CoRR, 2024

Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations.
CoRR, 2024

Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments.
CoRR, 2023

Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation.
CoRR, 2023

Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling.
Proceedings of the International Conference on Machine Learning, 2023

2022
Rethinking the Importance of Sampling in Physics-informed Neural Networks.
CoRR, 2022

Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM).
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
Beyond Observed Connections : Link Injection.
CoRR, 2020

Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020


  Loading...