66 citations · 87 across the 8 of their papers we have counts for
8 papers
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…
Distilling Calibrated Student from an Uncalibrated Teacher
Ishan Mishra, Sethu Vamsi Krishna, Deepak Mishra
Knowledge distillation is a common technique for improving the performance of a shallow student network by transferring information from a teacher network, which in general, is com…
Large Scale Time-Series Representation Learning via Simultaneous Low and High Frequency Feature Bootstrapping
Vandan Gorade, Azad Singh, Deepak Mishra
Learning representation from unlabeled time series data is a challenging problem. Most existing self-supervised and unsupervised approaches in the time-series domain do not capture…
Probabilistic Trust Intervals for Out of Distribution Detection
Gagandeep Singh, Ishan Mishra, Deepak Mishra
The ability of a deep learning network to distinguish between in-distribution (ID) and out-of-distribution (OOD) inputs is crucial for ensuring the reliability and trustworthiness…
Effect of The Latent Structure on Clustering with GANs
Deepak Mishra, Aravind Jayendran, Prathosh A. P
Generative adversarial networks (GANs) have shown remarkable success in generation of data from natural data manifolds such as images. In several scenarios, it is desirable that ge…
Target-Independent Domain Adaptation for WBC Classification using Generative Latent Search
Prashant Pandey, Prathosh AP, Vinay Kyatham +2
Automating the classification of camera-obtained microscopic images of White Blood Cells (WBCs) and related cell subtypes has assumed importance since it aids the laborious manual…