{ "schema_version": 1, "title": "Repro - Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning", "emoji": "🎯", "space_id": "rdubwiley/differentiable-optimization-layers-for-guaranteed-repro", "paper": { "arxiv_id": "2605.17118" }, "tags": [ "icml2026-repro", "paper-9SLQACsSbw" ], "updated_at": "2026-07-18T01:59:04+00:00", "root": { "slug": "index", "title": "Repro - Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning", "file": "pages/index.md", "children": [ { "slug": "claim-1-fairness-layer-as-differentiable-optimization-guarantees-chosen-notion-of-output-parity-in-neural-networks", "title": "Claim 1: Fairness layer as differentiable optimization guarantees chosen notion of output parity in neural networks.", "file": "pages/claim-1-fairness-layer-as-differentiable-optimization-guarantees-chosen-notion-of-output-parity-in-neural-networks/page.md", "children": [] }, { "slug": "claim-2-online-primal-dual-inference-provides-provable-aggregate-fairness-guarantees-for-streaming-predictions-with-arbitrarily", "title": "Claim 2: Online primal-dual inference provides provable aggregate fairness guarantees for streaming predictions with arbitrarily", "file": "pages/claim-2-online-primal-dual-inference-provides-provable-aggregate-fairness-guarantees-for-streaming-predictions-with-arbitrarily/page.md", "children": [] }, { "slug": "claim-3-fairness-layer-exhibits-characterized-differentiability-and-stability-properties-during-model-training-and-backpropagati", "title": "Claim 3: Fairness layer exhibits characterized differentiability and stability properties during model training and backpropagati", "file": "pages/claim-3-fairness-layer-exhibits-characterized-differentiability-and-stability-properties-during-model-training-and-backpropagati/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] }, "agent_view_tokens": 4846, "revision": "1784339944183169932" }