1 code implementation • COLING (TextGraphs) 2020 • Aditya Girish Pawate, Varun Madhavan, Devansh Chandak
In this work, we describe the system developed by a group of undergraduates from the Indian Institutes of Technology for the Shared Task at TextGraphs-14 on Multi-Hop Inference Explanation Regeneration (Jansen and Ustalov, 2020).
1 code implementation • 20 Nov 2023 • P Aditya Sreekar, Sahil Verma, Varun Madhavan, Abhishek Persad
Shipping cost of these packages are used on the day of shipping (day 0) to estimate profitability of sales.
no code implementations • 6 Feb 2023 • Cameron Gruich, Varun Madhavan, Yixin Wang, Bryan Goldsmith
It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches.
no code implementations • 28 May 2022 • Varun Madhavan, Adway Mitra, Partha Pratim Chakrabarti
An alternative is to develop an emulator, a surrogate model that can predict the Agent-Based Simulator's output based on its initial conditions and parameters.
no code implementations • 23 Mar 2022 • Ziming Liu, Varun Madhavan, Max Tegmark
We present a machine learning algorithm that discovers conservation laws from differential equations, both numerically (parametrized as neural networks) and symbolically, ensuring their functional independence (a non-linear generalization of linear independence).
1 code implementation • EMNLP (ArgMining) 2021 • Manav Nitin Kapadnis, Sohan Patnaik, Siba Smarak Panigrahi, Varun Madhavan, Abhilash Nandy
We present the system description for our submission towards the Key Point Analysis Shared Task at ArgMining 2021.
1 code implementation • 9 Oct 2021 • Varun Madhavan, Aditya Girish Pawate, Shraman Pal, Abhranil Chandra
Cognitively inspired Natural Language Pro-cessing uses human-derived behavioral datalike eye-tracking data, which reflect the seman-tic representations of language in the humanbrain to augment the neural nets to solve arange of tasks spanning syntax and semanticswith the aim of teaching machines about lan-guage processing mechanisms.