Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Chakravarty, Debashish"'
Entity Augmentation for Efficient Classification of Vertically Partitioned Data with Limited Overlap
Autor:
Amalanshu, Avi, Nagaswamy, Viswesh, Prudhvi, G. V. S. S., Sirvi, Yash, Chakravarty, Debashish
Vertical Federated Learning (VFL) is a machine learning paradigm for learning from vertically partitioned data (i.e. features for each input are distributed across multiple "guest" clients and an aggregating "host" server owns labels) without communi
Externí odkaz:
http://arxiv.org/abs/2406.17899
Autor:
N, Viswesh, Jadhav, Kaushal, Amalanshu, Avi, Mondal, Bratin, Waran, Sabaris, Sadhwani, Om, Kumar, Apoorv, Chakravarty, Debashish
The following work is a reproducibility report for CLRNet: Cross Layer Refinement Network for Lane Detection. The basic code was made available by the author. The paper proposes a novel Cross Layer Refinement Network to utilize both high and low leve
Externí odkaz:
http://arxiv.org/abs/2310.01142
Indoor motion planning focuses on solving the problem of navigating an agent through a cluttered environment. To date, quite a lot of work has been done in this field, but these methods often fail to find the optimal balance between computationally i
Externí odkaz:
http://arxiv.org/abs/2209.08663
Publikováno v:
ReScience C 8.2 (#34) 2022
This report covers our reproduction effort of the paper 'Differentiable Spatial Planning using Transformers' by Chaplot et al. . In this paper, the problem of spatial path planning in a differentiable way is considered. They show that their proposed
Externí odkaz:
http://arxiv.org/abs/2208.09536
Publikováno v:
RescienceC 2022
The following paper is a reproducibility report for "Social NCE: Contrastive Learning of Socially-aware Motion Representations" {\cite{liu2020snce}} published in ICCV 2021 as part of the ML Reproducibility Challenge 2021. The original code was made a
Externí odkaz:
http://arxiv.org/abs/2208.09284
The following paper is a reproducibility report for "Path Planning using Neural A* Search" published in ICML2 2021 as part of the ML Reproducibility Challenge 2021. The original paper proposes the Neural A* planner, and claims it achieves an optimal
Externí odkaz:
http://arxiv.org/abs/2208.04153
Autor:
Kalaria, Dvij, Maheshwari, Parv, Jha, Animesh, Issar, Arnesh Kumar, Chakravarty, Debashish, Anwar, Sohel, Towar, Andres
The paper presents a strategy for the control of anautonomous racing car on a pre-mapped track. Using a dynamic model of the vehicle, the optimal racing line is computed, taking track boundaries into account. With the optimal racing line as areferenc
Externí odkaz:
http://arxiv.org/abs/2109.07105
An artificial neural network-based integrated tilt control system for narrow electric three-wheelers
Publikováno v:
In Expert Systems With Applications 15 March 2024 238 Part C
Autor:
Issar, Arnesh Kumar, Mali, Kirtan, Mehta, Aryan, Uppal, Karan, Mishra, Saurabh, Chakravarty, Debashish
The following paper is a reproducibility report for "FDA: Fourier Domain Adaptation for Semantic Segmentation" published in the CVPR 2020 as part of the ML Reproducibility Challenge 2020. The original code was made available by the author. The well-c
Externí odkaz:
http://arxiv.org/abs/2104.14749
Autor:
Patnaik, Adarsh, Patel, Manthan, Mohta, Vibhakar, Shah, Het, Agrawal, Shubh, Rathore, Aditya, Malik, Ritwik, Chakravarty, Debashish, Bhattacharya, Ranjan
This article is an overview of the various literature on path tracking methods and their implementation in simulation and realistic operating environments.The scope of this study includes analysis, implementation,tuning, and comparison of some select
Externí odkaz:
http://arxiv.org/abs/2012.02978