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Spectral Evolution and Invariance in Linear-width Neural Networks
We investigate the spectral properties of linear-width feed-forward neural networks, where the sample size is asymptotically proportional to network width.
Cross-Scale MAE: AT ale of Multi-Scale Exploitation in Remote Sensing Maofeng T ang
We present Cross-Scale MAE, a self-supervised model built upon the Masked Auto-Encoder (MAE).
Appendix Table of Contents
Our datasets and code are available via the following links: Github: https://github.com/NREL/BuildingsBench As described in Sec. 3 and Sec. 4, Buildings-900K and the BuildingsBench benchmark datasets are B.1 Motivation Q: For what purpose was the dataset created? It specifically addresses a lack of appropriately sized and diverse datasets for pretraining STLF models. We emphasize that the EULP was not originally developed for studying STLF. Rather, it was developed as a general resource to "...help electric utilities, grid operators, manufacturers, Q: Who created the dataset (e.g., which team, research group) and on behalf of which entity Q: Who funded the creation of the dataset?
Buildings Bench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
Short-term load forecasting (STLF), which typically ranges from hour-ahead to a few days ahead, plays a multitude of critical roles.
These freaky fish use their forehead teeth to have better sex
Amazon Prime Day is live. See the best deals HERE. Plus landmine-detecting rats and other weird things we learned this week. Let's talk about (ratfish) sex, baby. Breakthroughs, discoveries, and DIY tips sent every weekday. What's the weirdest thing you learned this week?
Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
Locally interpretable model agnostic explanations (LIME) method is one of the most popular methods used to explain black-box models at a per example level.
Matrix Compression via Randomized Low Rank and Low Precision Factorization
Matrices are exceptionally useful in various fields of study as they provide a convenient framework to organize and manipulate data in a structured manner.
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
We present a case study on malware detection--a binary classification problem on byte sequences where classifier evasion is a well-established threat model.