no code implementations • VarDial (COLING) 2022 • Abhijnan Nath, Rahul Ghosh, Nikhil Krishnaswamy
In this paper, we propose a method to detect if words in two similar languages, Assamese and Bengali, are cognates.
no code implementations • 29 Jan 2024 • Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David Mulla, Vipin Kumar
We finally discuss the impact of weather by correlating our results with crop phenology to show that WSTATT is able to capture physical properties of crop growth.
no code implementations • 16 Nov 2023 • Sayan Putatunda, Anwesha Bhowmik, Girish Thiruvenkadam, Rahul Ghosh
Nudge marketing is a subtle way for an ecommerce company to help their customers make better decisions without hesitation.
no code implementations • 7 Oct 2023 • Arvind Renganathan, Rahul Ghosh, Ankush Khandelwal, Vipin Kumar
We present a Task-aware modulation using Representation Learning (TAM-RL) framework that enhances personalized predictions in few-shot settings for heterogeneous systems when individual task characteristics are not known.
no code implementations • 3 Oct 2023 • Somya Sharma Chatterjee, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher Duffy, Vipin Kumar
Our inverse model offers 3\% improvement in R$^2$ for the inverse model (basin characteristic estimation) and 6\% for the forward model (streamflow prediction).
no code implementations • 19 Sep 2023 • Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar
Accurate long-term predictions are the foundations for many machine learning applications and decision-making processes.
no code implementations • 16 Feb 2023 • Rahul Ghosh, HaoYu Yang, Ankush Khandelwal, Erhu He, Arvind Renganathan, Somya Sharma, Xiaowei Jia, Vipin Kumar
However, these entity characteristics are not readily available in many real-world scenarios, and different ML methods have been proposed to infer these characteristics from the data.
no code implementations • 1 Jan 2023 • Leikun Yin, Rahul Ghosh, Chenxi Lin, David Hale, Christoph Weigl, James Obarowski, Junxiong Zhou, Jessica Till, Xiaowei Jia, Troy Mao, Vipin Kumar, Zhenong Jin
In particular, we developed a SpatioTemporal Classification with Attention (STCA) model to map the distribution of cashew plantations, which can fully capture texture information from discriminative time steps during a growing season.
1 code implementation • 15 Oct 2022 • Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael Steinbach, Christopher Duffy, John Nieber, Vipin Kumar
To address this issue, we further propose a new strategy which augments a training segment with an initial value of the target variable from the timestep right before the starting of the training segment.
no code implementations • 14 Oct 2022 • Praveen Ravirathinam, Rahul Ghosh, Ke Wang, Keyang Xuan, Ankush Khandelwal, Hilary Dugan, Paul Hanson, Vipin Kumar
Using this large unlabelled dataset, we first show how a spatiotemporal representation is better compared to just spatial or temporal representation.
no code implementations • 12 Oct 2022 • Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher Duffy, Vipin Kumar
We propose uncertainty based learning method that offers 6\% improvement in $R^2$ for streamflow prediction (forward modeling) from inverse model inferred basin characteristic estimates, 17\% reduction in uncertainty (40\% in presence of noise) and 4\% higher coverage rate for basin characteristics.
no code implementations • 14 Sep 2021 • Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Chris Duffy, John Neiber, Vipin Kumar
Furthermore, we show that KGSSL is relatively more robust to distortion than baseline methods, and outperforms the baseline model by 35\% when plugging in KGSSL inferred characteristics.
no code implementations • 16 Aug 2021 • Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Vipin Kumar
In many applications, finding adequate labeled data to train predictive models is a major challenge.
no code implementations • 16 Aug 2021 • Rahul Ghosh, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar
Common techniques of addressing this issue, based on the underlying idea of pre-training the Deep Neural Networks (DNN) on freely available large datasets, cannot be used for Remote Sensing due to the unavailability of such large-scale labeled datasets and the heterogeneity of data sources caused by the varying spatial and spectral resolution of different sensors.
no code implementations • 26 Jul 2021 • Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Ankush Khandelwal, David Mulla, Vipin Kumar
Mapping and monitoring crops is a key step towards sustainable intensification of agriculture and addressing global food security.
no code implementations • 2 May 2021 • Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar
The availability of massive earth observing satellite data provide huge opportunities for land use and land cover mapping.
no code implementations • 3 Mar 2021 • Rahul Ghosh, Xiaowei Jia, Vipin Kumar
Land cover mapping is essential for monitoring global environmental change and managing natural resources.
no code implementations • 11 Jan 2021 • Bijan Bagchi, Rahul Ghosh
We investigate the most general form of the one-dimensional Dirac Hamiltonian $H_D$ in the presence of scalar and pseudoscalar potentials.
Quantum Physics High Energy Physics - Theory Mathematical Physics Mathematical Physics
no code implementations • COLING 2020 • Kshitij Tayal, Rahul Ghosh, Vipin Kumar
To our knowledge, this is the first time such a comprehensive study in text classification encircling popular models and model-agnostic loss methods has been conducted.
no code implementations • 3 Jan 2020 • Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar
Many real-world phenomena are observed at multiple resolutions.