End-to-End Weak Supervision SR Cachay, B Boecking, A Dubrawski NeurIPS, 2021 | 38* | 2021 |
The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks SR Cachay, E Erickson, AFC Bucker, E Pokropek, W Potosnak, S Bire, ... arXiv preprint arXiv:2104.05089, 2021 | 21 | 2021 |
Graph Neural Networks for Improved El Niño Forecasting S Rühling Cachay, E Erickson, AFC Bucker, E Pokropek, W Potosnak, ... NeurIPS 2020 workshop on Tackling Climate Change with Machine Learning, 2020 | 19* | 2020 |
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models SR Cachay, V Ramesh, JNS Cole, H Barker, D Rolnick NeurIPS Datasets and Benchmarks Track, 2021 | 15 | 2021 |
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting SR Cachay, B Zhao, H James, R Yu NeurIPS, 2023 | 12 | 2023 |
Dependency Structure Misspecification in Multi-Source Weak Supervision Models SR Cachay, B Boecking, A Dubrawski ICLR 2021 workshop on Weakly Supervised Learning (oral presentation), 2021 | 8 | 2021 |
ClimFormer–A Spherical Transformer Model for Long-term Climate Projections SR Cachay, P Mitra, H Hirasawa, S Kim, S Hazarika, D Hingmire, P Rasch, ... Proceedings of the Machine Learning and the Physical Sciences Workshop …, 2022 | 1 | 2022 |
Graph Deep Learning for Long Range Forecasting S Rühling Cachay, E Erickson, AFC Bucker, E Pokropek, W Potosnak, ... EGU21, 2021 | 1 | 2021 |
HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns S Hazarika, H Hirasawa, S Kim, K Ramea, SR Cachay, P Mitra, ... 2023 IEEE Visualization and Visual Analytics (VIS), 226-230, 2023 | | 2023 |
Climate Intervention Analysis using AI Model Guided by Statistical Physics Principles S Kim, K Ramea, SR Cachay, H Hirasawa, S Hazarika, D Hingmire, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | | 2023 |
Accelerating exploration of Marine Cloud Brightening impacts on tipping points Using an AI Implementation of Fluctuation-Dissipation Theorem H Hirasawa, S Kim, P Mitra, S Hazarika, S Ruhling-Cachay, D Hingmire, ... arXiv preprint arXiv:2302.01957, 2023 | | 2023 |
ClimFormer: building an attention-based climate emulator P Mitra, SR Cachay, SK Kim, S Hazarika, K Ramea, DS Hingmire, ... Fall Meeting 2022, 2022 | | 2022 |
On incorporating first principles based physical conservation laws into global climate emulators P Mitra, DS Hingmire, H Hirasawa, SR Cachay, S Hazarika, SK Kim, ... Fall Meeting 2022, 2022 | | 2022 |
AI assisted evaluation of ESMs in simulating observed cloud climate interactions DS Hingmire, H Hirasawa, HA Singh, SR Cachay, SK Kim, P Mitra, ... AGU Fall Meeting Abstracts 2022, A25I-1844, 2022 | | 2022 |
Marine Cloud Brightening Intervention Optimization using a Hybrid AI Approach HA Singh, H Hirasawa, D Hingmire, S Hazarika, SK Kim, SR Cachay, ... AGU Fall Meeting Abstracts 2022, GC16A-03, 2022 | | 2022 |
Interactive Visual Analytics to Study the Impacts of Cloud Radiative Properties on Climate Patterns S Hazarika, K Ramea, SK Kim, P Mitra, SR Cachay, H Hirasawa, ... AGU Fall Meeting Abstracts 2022, IN41C-01, 2022 | | 2022 |
Projecting the Climate Response to Forcings with Machine Learning Models using the Fluctuation-Dissipation Relation H Hirasawa, S Hazarika, S Kim, P Mitra, SR Cachay, D Hingmire, ... AGU23, 0 | | |
Model Misspecification in Multiple Weak Supervision SR Cachay, B Boecking, A Dubrawski LatinX in AI workshop at NeurIPS, 0 | | |