47 citations · 54 across the 6 of their papers we have counts for
8 papers
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation
Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu +3
Recently, the fundamental problem of unsupervised domain adaptation (UDA) on 3D point clouds has been motivated by a wide variety of applications in robotics, virtual reality, and…
GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering
Dhaval Taunk, Lakshya Khanna, Pavan Kandru +3
Commonsense question-answering (QA) methods combine the power of pre-trained Language Models (LM) with the reasoning provided by Knowledge Graphs (KG). A typical approach collects…
Person Re-Identification with a Locally Aware Transformer
Charu Sharma, Siddhant R. Kapil, David Chapman
Person Re-Identification is an important problem in computer vision-based surveillance applications, in which the same person is attempted to be identified from surveillance photog…
Self-Supervised Few-Shot Learning on Point Clouds
Charu Sharma, Manohar Kaul
The increased availability of massive point clouds coupled with their utility in a wide variety of applications such as robotics, shape synthesis, and self-driving cars has attract…
Simplicial Complex based Point Correspondence between Images warped onto Manifolds
Charu Sharma, Manohar Kaul
Recent increase in the availability of warped images projected onto a manifold (e.g., omnidirectional spherical images), coupled with the success of higher-order assignment methods…
Learning Representations using Spectral-Biased Random Walks on Graphs
Charu Sharma, Jatin Chauhan, Manohar Kaul
Several state-of-the-art neural graph embedding methods are based on short random walks (stochastic processes) because of their ease of computation, simplicity in capturing complex…
Solving Partial Assignment Problems using Random Clique Complexes
Charu Sharma, Deepak Nathani, Manohar Kaul
We present an alternate formulation of the partial assignment problem as matching random clique complexes, that are higher-order analogues of random graphs, designed to provide a s…
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
Deepak Nathani, Jatin Chauhan, Charu Sharma +1
The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of re…