|
108 | 108 | ], |
109 | 109 | "type": "tool", |
110 | 110 | "year": 2025, |
111 | | - "github_url": "https://github.com/VectorInstitute/fair-sense-ai" |
| 111 | + "github_url": "https://github.com/VectorInstitute/fair-sense-ai", |
| 112 | + "package_name": "fair-sense-ai" |
112 | 113 | }, |
113 | 114 | { |
114 | 115 | "name": "fed-rag", |
|
127 | 128 | "type": "tool", |
128 | 129 | "year": 2025, |
129 | 130 | "github_url": "https://github.com/VectorInstitute/fed-rag", |
| 131 | + "package_name": "fed-rag", |
130 | 132 | "paper_url": "https://doi.org/10.5281/zenodo.15092361", |
131 | 133 | "bibtex": "fajardo2025fedrag" |
132 | 134 | }, |
|
183 | 185 | "implementations": [ |
184 | 186 | { |
185 | 187 | "name": "LIME", |
186 | | - "url": "https://christophm.github.io/interpretable-ml-book/lime.html" |
| 188 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/LIME" |
187 | 189 | }, |
188 | 190 | { |
189 | 191 | "name": "SHAP", |
190 | | - "url": "https://arxiv.org/abs/1705.07874" |
| 192 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/SHAP" |
191 | 193 | }, |
192 | 194 | { |
193 | 195 | "name": "PDP (Partial Dependence Plot)", |
194 | | - "url": "https://scikit-learn.org/stable/modules/partial_dependence.html" |
| 196 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/partial_dependence_plots" |
195 | 197 | }, |
196 | 198 | { |
197 | 199 | "name": "ALE (Accumulated Local Effects)", |
198 | | - "url": "https://christophm.github.io/interpretable-ml-book/ale.html" |
| 200 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/acc_local_effects" |
199 | 201 | }, |
200 | 202 | { |
201 | 203 | "name": "Integrated Gradients", |
202 | | - "url": "https://www.tensorflow.org/tutorials/interpretability/integrated_gradients" |
| 204 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/integrated_gradients" |
203 | 205 | }, |
204 | 206 | { |
205 | 207 | "name": "Counterfactual Explanations", |
206 | | - "url": "https://christophm.github.io/interpretable-ml-book/counterfactual.html" |
| 208 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Post-hoc/counterfactual" |
207 | 209 | }, |
208 | 210 | { |
209 | 211 | "name": "Generalized Additive Model", |
210 | | - "url": "https://en.wikipedia.org/wiki/Generalized_additive_model" |
| 212 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Intepretable-models/Tabular/GAM" |
211 | 213 | }, |
212 | 214 | { |
213 | 215 | "name": "Neural Additive Model", |
214 | | - "url": "https://arxiv.org/abs/2004.13912" |
| 216 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Intepretable-models/Tabular/NAM-NodeGAM" |
215 | 217 | }, |
216 | 218 | { |
217 | 219 | "name": "Explainable Boosting Machine", |
218 | | - "url": "https://interpret.ml/docs/ebm.html" |
| 220 | + "url": "https://github.com/VectorInstitute/interpretability/tree/main/reference_implementations/Intepretable-models/Tabular/EBM" |
219 | 221 | } |
220 | 222 | ], |
221 | 223 | "public_datasets": [ |
|
380 | 382 | "implementations": [ |
381 | 383 | { |
382 | 384 | "name": "AWS", |
383 | | - "url": "https://aws.amazon.com/" |
| 385 | + "url": "https://github.com/VectorInstitute/ai-deployment/tree/main/implementations/aws" |
384 | 386 | }, |
385 | 387 | { |
386 | 388 | "name": "GCP", |
387 | | - "url": "https://cloud.google.com/" |
| 389 | + "url": "https://github.com/VectorInstitute/ai-deployment/tree/main/implementations/gcp" |
388 | 390 | } |
389 | 391 | ], |
390 | 392 | "type": "bootcamp", |
|
503 | 505 | ], |
504 | 506 | "type": "tool", |
505 | 507 | "year": 2024, |
506 | | - "github_url": "https://github.com/VectorInstitute/cyclops" |
| 508 | + "github_url": "https://github.com/VectorInstitute/cyclops", |
| 509 | + "package_name": "pycyclops" |
507 | 510 | }, |
508 | 511 | { |
509 | 512 | "name": "diffusion-models", |
|
543 | 546 | ], |
544 | 547 | "type": "bootcamp", |
545 | 548 | "year": 2024, |
546 | | - "github_url": "https://github.com/VectorInstitute/diffusion_models" |
| 549 | + "github_url": "https://github.com/VectorInstitute/diffusion-models" |
547 | 550 | }, |
548 | 551 | { |
549 | 552 | "name": "finetuning-and-alignment", |
|
669 | 672 | ], |
670 | 673 | "type": "tool", |
671 | 674 | "year": 2024, |
672 | | - "github_url": "https://github.com/VectorInstitute/fl4health" |
| 675 | + "github_url": "https://github.com/VectorInstitute/fl4health", |
| 676 | + "package_name": "fl4health" |
673 | 677 | }, |
674 | 678 | { |
675 | 679 | "name": "florist", |
|
858 | 862 | "type": "bootcamp", |
859 | 863 | "year": 2024, |
860 | 864 | "github_url": "https://github.com/VectorInstitute/retrieval-augmented-generation", |
861 | | - "platform_url": "https://89kc2habps6ig.pit-1.try.coder.app/templates/rag-bootcamp/" |
| 865 | + "package_name": "aieng-rag-utils" |
862 | 866 | }, |
863 | 867 | { |
864 | 868 | "name": "self-supervised-learning", |
|
867 | 871 | "implementations": [ |
868 | 872 | { |
869 | 873 | "name": "Internal Contrastive Learning (ICL) + Latent Outlier Exposure (LOE)", |
870 | | - "url": "https://proceedings.mlr.press/v162/qiu22b/qiu22b.pdf" |
| 874 | + "url": "https://github.com/VectorInstitute/self-supervised-learning/tree/main/src/contrastive_learning" |
871 | 875 | }, |
872 | 876 | { |
873 | 877 | "name": "SimMTM", |
874 | | - "url": "https://arxiv.org/abs/2302.00861" |
| 878 | + "url": "https://github.com/VectorInstitute/self-supervised-learning/tree/main/src/masked_modelling/simmtm" |
875 | 879 | }, |
876 | 880 | { |
877 | 881 | "name": "TabRet", |
878 | | - "url": "https://arxiv.org/abs/2303.15747" |
| 882 | + "url": "https://github.com/VectorInstitute/self-supervised-learning/tree/main/src/masked_modelling/tabret" |
879 | 883 | }, |
880 | 884 | { |
881 | 885 | "name": "Data2Vec", |
882 | | - "url": "https://arxiv.org/abs/2202.03555" |
| 886 | + "url": "https://github.com/VectorInstitute/self-supervised-learning/tree/main/src/self_distillation" |
883 | 887 | } |
884 | 888 | ], |
885 | 889 | "public_datasets": [ |
|
903 | 907 | "type": "tool", |
904 | 908 | "year": 2024, |
905 | 909 | "github_url": "https://github.com/VectorInstitute/vector-inference", |
| 910 | + "package_name": "vec-inf", |
906 | 911 | "implementations": [ |
907 | 912 | "CLI", |
908 | 913 | "Python API", |
|
1036 | 1041 | ], |
1037 | 1042 | "totalImplementations": 136, |
1038 | 1043 | "yearsOfResearch": 7, |
1039 | | - "lastUpdated": "2025-11-25T15:22:49.432085" |
| 1044 | + "lastUpdated": "2025-11-26T21:41:00.884001" |
1040 | 1045 | } |
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