1 code implementation • 5 Feb 2024 • Rohin Manvi, Samar Khanna, Marshall Burke, David Lobell, Stefano Ermon
Initially, we demonstrate that LLMs are capable of making accurate zero-shot geospatial predictions in the form of ratings that show strong monotonic correlation with ground truth (Spearman's $\rho$ of up to 0. 89).
no code implementations • 6 Dec 2023 • Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David Lobell, Stefano Ermon
Our method outperforms previous state-of-the-art methods for satellite image generation and is the first large-scale $\textit{generative}$ foundation model for satellite imagery.
1 code implementation • 10 Oct 2023 • Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David Lobell, Stefano Ermon
With GeoLLM, we observe that GPT-3. 5 outperforms Llama 2 and RoBERTa by 19% and 51% respectively, suggesting that the performance of our method scales well with the size of the model and its pretraining dataset.
1 code implementation • 29 Sep 2023 • Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
However, for many applications such as image editing, the model input comes from a distribution that is not random noise.
no code implementations • 26 Aug 2023 • Samar Khanna, Skanda Vaidyanath, Akash Velu
For instance, given a network that has been trained on a source task, we would like to re-train this network on a similar, yet different, target task while maintaining its performance on the source task.
no code implementations • 20 Jul 2023 • Rylan Schaeffer, Kateryna Pistunova, Samar Khanna, Sarthak Consul, Sanmi Koyejo
We find that the logically \textit{invalid} reasoning prompts do indeed achieve similar performance gains on BBH tasks as logically valid reasoning prompts.
no code implementations • 17 Jul 2022 • Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon
Unsupervised pre-training methods for large vision models have shown to enhance performance on downstream supervised tasks.
1 code implementation • 14 Apr 2022 • Samar Khanna, Bram Wallace, Kavita Bala, Bharath Hariharan
Geographic variance in satellite imagery impacts the ability of machine learning models to generalise to new regions.