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Found 4 papers, 1 papers with code
Neural Embedding Compression For Efficient Multi-Task Earth Observation Modelling
We introduce Neural Embedding Compression (NEC), based on the transfer of compressed embeddings to data consumers instead of raw data.
Foundation Models for Generalist Geospatial Artificial Intelligence
This paper introduces a first-of-a-kind framework for the efficient pre-training and fine-tuning of foundational models on extensive geospatial data.
Video Compression With Entropy-Constrained Neural Representations
This performance gap can be explained by the fact that current NVR methods: i) use architectures that do not efficiently obtain a compact representation of temporal and spatial information; and ii) minimize rate and distortion disjointly (first overfitting a network on a video and then using heuristic techniques such as post-training quantization or weight pruning to compress the model).
Measuring the False Sense of Security
Recently, several papers have demonstrated how widespread gradient masking is amongst proposed adversarial defenses.
