Papers
(α-β denotes alphabetical order and * denotes equal contribution)
Learning general Gaussian mixtures with efficient score matching
PDF
(α-β) Sitan Chen, Vasilis Kontonis,
Preprint
Causal Language Modeling can Elicit Search and Reasoning Capabilities on Logic Puzzles
PDF
, Nishanth Dikkala, Xin Wang, Rina Panigrahy
NeurIPS 2024 | Conference on Neural Information Processing Systems
Unrolled denoising networks provably learn optimal Bayesian inference
PDF
Aayush Karan*, *, Sitan Chen, Yonina C. Eldar
NeurIPS 2024 | Conference on Neural Information Processing Systems
Simple Mechanisms for Representing, Indexing and Manipulating Concepts
PDF
(α-β)Yuanzhi Li, Raghu Meka, Rina Panigrahy,
Preprint
Learning Mixtures of Gaussians Using the DDPM Objective
PDF
Poster
, Sitan Chen, Adam Klivans
NeurIPS 2023 | Conference on Neural Information Processing Systems
Ambient Diffusion: Learning Clean Distributions From Corrupted Data
PDF
Code
Giannis Daras, , Yuval Dagan, Aravind Gollakota, Alexandros G. Dimakis, Adam Klivans
NeurIPS 2023 | Conference on Neural Information Processing Systems
Learning and Generalization in Overparameterized Normalizing Flows
PDF
Poster
Code
, Amit Deshpande, Navin Goyal
AISTATS 2022 | International Conference on Artificial Intelligence and Statistics
RISAN: Robust Instance Specific Deep Abstention Network
PDF
Bhavya Kalra, , Naresh Manwani
UAI, 2021
Selected for Oral presentation
Rawlsian Fair Adaptation of Deep Learning Classifiers
PDF
, Pooja Gupta, Amit Deshpande, Chiranjib Bhattacharyya
AIES, 2021
Online Active Learning of Reject Option Classifiers
PDF
, Naresh Manwani
AAAI, 2020
Selected for Oral presentation
Sparse Reject Option Classifier using Successive Linear Programming
PDF
, Naresh Manwani
AAAI, 2019
Selected for Oral presentation
Ingredients for happiness: Modeling constructs via semi-supervised content driven inductive transfer learning
PDF
, Naresh Manwani
AFFCON workshop @ AAAI, 2019
PLUME: Polyhedral Learning Using Mixture of Experts
PDF
, PS Sastry, Naresh Manwani
Preprint
Wepage inspired by minimal research theme.