2 citations · 4 across the 9 of their papers we have counts for
9 papers
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral +2
Do contemporary diffusion models preserve the class geometry of hyperspherical data? Standard diffusion models rely on isotropic Gaussian noise in the forward process, inherently f…
LitMAS: A Lightweight and Generalized Multi-Modal Anti-Spoofing Framework for Biometric Security
Nidheesh Gorthi, Kartik Thakral, Rishabh Ranjan +2
Biometric authentication systems are increasingly being deployed in critical applications, but they remain susceptible to spoofing. Since most of the research efforts focus on moda…
Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models
Kartik Thakral, Tamar Glaser, Tal Hassner +2
Existing unlearning algorithms in text-to-image generative models often fail to preserve the knowledge of semantically related concepts when removing specific target concepts: a ch…
Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion
Kartik Thakral, Tamar Glaser, Tal Hassner +2
How can we effectively unlearn selected concepts from pre-trained generative foundation models without resorting to extensive retraining? This research introduces `continual unlear…
HyperSpaceX: Radial and Angular Exploration of HyperSpherical Dimensions
Chiranjeev Chiranjeev, Muskan Dosi, Kartik Thakral +2
Traditional deep learning models rely on methods such as softmax cross-entropy and ArcFace loss for tasks like classification and face recognition. These methods mainly explore ang…
On Responsible Machine Learning Datasets with Fairness, Privacy, and Regulatory Norms
Surbhi Mittal, Kartik Thakral, Richa Singh +4
Artificial Intelligence (AI) has made its way into various scientific fields, providing astonishing improvements over existing algorithms for a wide variety of tasks. In recent yea…