Hacker News
- A Short Chronology of Deep Learning for Tabular Data https://sebastianraschka.com/blog/2022/deep-learning-for-tabular-data.html 14 comments
- [P] A Short Chronology Of Deep Learning For Tabular Data https://sebastianraschka.com/blog/2022/deep-learning-for-tabular-data.html 4 comments machinelearning
Linking pages
- AI and Open Source in 2023 - by Sebastian Raschka, PhD https://magazine.sebastianraschka.com/p/ai-and-open-source-in-2023 67 comments
- Keeping Up With AI Research And News https://sebastianraschka.com/blog/2023/keeping-up-with-ai.html 22 comments
- GitHub - r0f1/datascience: Curated list of Python resources for data science. https://github.com/r0f1/datascience 0 comments
- Ahead of AI #2: Transformers, Fast and Slow | Revue https://newsletter.sebastianraschka.com/issues/ahead-of-ai-2-transformers-fast-and-slow-1402662 0 comments
- Ahead of AI #4: A Big Year For AI - by Sebastian Raschka https://magazine.sebastianraschka.com/p/ahead-of-ai-4-a-big-year-for-ai 0 comments
- Influential Machine Learning Papers Of 2022 https://sebastianraschka.com/blog/2023/top10-papers-2022.html 0 comments
Linked pages
- [2207.08815] Why do tree-based models still outperform deep learning on tabular data? https://arxiv.org/abs/2207.08815 266 comments
- [2106.11189] Well-tuned Simple Nets Excel on Tabular Datasets https://arxiv.org/abs/2106.11189 114 comments
- [2207.01848] TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second https://arxiv.org/abs/2207.01848 48 comments
- [2203.05556] On Embeddings for Numerical Features in Tabular Deep Learning https://arxiv.org/abs/2203.05556 33 comments
- [1908.07442] TabNet: Attentive Interpretable Tabular Learning https://arxiv.org/abs/1908.07442 17 comments
- [2106.02584] Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning https://arxiv.org/abs/2106.02584 4 comments
- GitHub - jrzaurin/pytorch-widedeep: A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch https://github.com/jrzaurin/pytorch-widedeep 1 comment
- [2210.06280] Language Models are Realistic Tabular Data Generators https://arxiv.org/abs/2210.06280 1 comment
- [2106.03253] Tabular Data: Deep Learning is Not All You Need https://arxiv.org/abs/2106.03253 0 comments
- GitHub - ml-jku/hopular: Hopular: Modern Hopfield Networks for Tabular Data https://github.com/ml-jku/hopular 0 comments
- [1909.06312] Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data https://arxiv.org/abs/1909.06312 0 comments
- [2206.00664] Hopular: Modern Hopfield Networks for Tabular Data https://arxiv.org/abs/2206.00664 0 comments
- [2110.01889] Deep Neural Networks and Tabular Data: A Survey https://arxiv.org/abs/2110.01889 0 comments
- AutoGluon 0.7.0 documentation https://auto.gluon.ai/stable/index.html 0 comments
- Porto Seguro’s Safe Driver Prediction | Kaggle https://www.kaggle.com/competitions/porto-seguro-safe-driver-prediction/discussion/44629 0 comments
- Hopfield network - Wikipedia https://en.wikipedia.org/wiki/Hopfield_network 0 comments
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