{"url":"/method/gandalf","slug":"gandalf","name":"GANDALF","full_name":"Gated Adaptive Network for Deep Automated Learning of Features","full_name_withheld":false,"description_markdown":"We propose a novel high-performance, interpretable, and parameter \\& computationally efficient deep learning architecture for tabular data, Gated Adaptive Network for Deep Automated Learning of Features (GANDALF). GANDALF relies on a new tabular processing unit with a gating mechanism and in-built feature selection called Gated Feature Learning Unit (GFLU) as a feature representation learning unit. We demonstrate that GANDALF outperforms or stays at-par with SOTA approaches like XGBoost, SAINT, FT-Transformers, etc. by experiments on multiple established public benchmarks. We have made available the code at github.com/manujosephv/pytorch_tabular under MIT License.","description_state":"present","introduced_year":null,"introduced_by":{"title":"GANDALF: Gated Adaptive Network for Deep Automated Learning of Features","paper":"/paper/gate-gated-additive-tree-ensemble-for-tabular","first_author":"Manu Joseph","n_authors":2,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/gate-gated-additive-tree-ensemble-for-tabular"},"source":{"url":"https://arxiv.org/abs/2207.08548v6","title":"GANDALF: Gated Adaptive Network for Deep Automated Learning of Features","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Deep Tabular Learning","url":"/methods/category/deep-tabular-learning","pwc_aliases":[]}],"n_papers_tagged":4,"archive_num_papers":4,"papers_newest_first":[{"paper":null,"title":"Disentangling stellar atmospheric parameters in astronomical spectra using Generative Adversarial Neural Networks","date":"2025-01-20","arxiv_id":"2501.11762","n_code_links":0,"syntology":null},{"paper":null,"title":"A Survey on Deep Tabular Learning","date":"2024-10-15","arxiv_id":"2410.12034","n_code_links":0,"syntology":null},{"paper":null,"title":"Learning label-label correlations in Extreme Multi-label Classification via Label Features","date":"2024-05-03","arxiv_id":"2405.04545","n_code_links":0,"syntology":null},{"paper":"/paper/gate-gated-additive-tree-ensemble-for-tabular","title":"GANDALF: Gated Adaptive Network for Deep Automated Learning of Features","date":"2022-07-18","arxiv_id":"2207.08548","n_code_links":2,"syntology":{"ran":2,"of":14,"unverified":12,"pointer_only":0}}],"papers_shown":4,"tasks":[{"task":"/task/feature-selection","name":"feature selection","papers":2},{"task":"/task/denoising","name":"Denoising","papers":1},{"task":"/task/dimensionality-reduction","name":"Dimensionality Reduction","papers":1},{"task":"/task/extreme-multi-label-classification","name":"Extreme Multi-Label Classification","papers":1},{"task":"/task/multi-label-classification-2","name":"MUlTI-LABEL-ClASSIFICATION","papers":1},{"task":"/task/multi-label-text-classification-1","name":"Multi Label Text Classification","papers":1},{"task":"/task/multi-label-classification","name":"Multi-Label Classification","papers":1},{"task":"/task/multi-label-text-classification","name":"Multi-Label Text Classification","papers":1},{"task":"/task/product-recommendation","name":"Product Recommendation","papers":1},{"task":"/task/representation-learning","name":"Representation Learning","papers":1},{"task":"/task/survey","name":"Survey","papers":1},{"task":"/task/text-classification","name":"Text Classification","papers":1},{"task":"/task/transfer-learning","name":"Transfer Learning","papers":1},{"task":"/task/regression-1","name":"regression","papers":1},{"task":"/task/tabular-classification","name":"tabular-classification","papers":1},{"task":"/task/text-classification-1","name":"text-classification","papers":1}],"tasks_shown":16,"n_tasks":16,"usage_by_year":[{"year":"2022","papers":1},{"year":"2024","papers":2},{"year":"2025","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/gandalf"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}