Failure-mode index

Search what already failed

A searchable index of real negative results, null findings, and replication failures from the published literature — so you can learn what didn't work before repeating it.

All Replication Failure Negative / Null Result Report Failed Experiment Report Abandoned Hypothesis Methods Dead-End Short Note Null Dataset Protocol

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record (title, authors, DOI) compiled from open scholarly databases, with the abstract shown in full only where the paper is openly licensed (e.g. Creative Commons); otherwise a short excerpt is shown for reference under fair use. WASTE classifies each work by failure type; classifications are automated and approximate.

By fieldMedicine 12,301 Computer Science 753 Biochemistry, Genetics and Molecular Biology 443 Social Sciences 312 Psychology 309 Physics 280 Neuroscience 258 Economics, Econometrics and Finance 209 Environmental Science 186 Mathematics 161 Agricultural and Biological Sciences 151 Engineering 150

1 result in Null Dataset for "deep learning"

Null DatasetOpen accessEngineering

ATRNet-STAR: A Large Dataset and Benchmark Toward Remote Sensing Object Recognition in the Wild

Yongxiang Liu, Weijie Li, Li Liu et al. · 2026 · IEEE Transactions on Pattern Analysis and Machine Intelligence

The absence of publicly available, large-scale, high-quality datasets for Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has significantly hindered the application of rapidly advancing deep learning techniques, which hold huge potential to unlock new capabilities in this field. This is primarily because collecting large volumes of diverse target samples from SAR images is prohibitively expensive, largely due to privacy concerns, the characteristics of microwave radar imagery perception, and the need for specialized expertise in data annotation. Throughout the history of SAR AT

View details →DOI: 10.1109/tpami.2026.3658649Cited by 10