kaft-neurips.git - Unnamed repository; edit this file 'description' to name the repository.

Age	Commit message (Collapse)	Author
15 hours	Global rename GRAFT → KAFT (incl. internal class + filenames)	YurenHao0426
	- src/trainers.py: GraphGrAPETrainer → KAFTTrainer; module docstring + comments. VanillaGrAPETrainer kept as-is (it is a separate control method, not KAFT). - experiments/: all 19 runners pick up the new class name; result keys ('Cora_GRAFT' etc) become 'Cora_KAFT'; OUT_DIRs renamed (e.g. bp_graft_depth_20seeds → bp_kaft_depth_20seeds). - figures/: data-lookup keys + display labels both 'KAFT'; output filename graft_depth_sweep.{pdf,png} → kaft_depth_sweep.{pdf,png}. - File rename: experiments/run_bp_graft_depth.py → run_bp_kaft_depth.py; figures/graft_depth_sweep.pdf → kaft_depth_sweep.pdf. - README aligned. Imports verified: from src.trainers import KAFTTrainer succeeds.
15 hours	Initial release: GRAFT (KAFT) — NeurIPS 2026 submission code	YurenHao0426
	Topology-factorized Jacobian-aligned feedback for deep GNNs. Includes: - src/: GraphGrAPETrainer (KAFT) + BP / DFA / DFA-GNN / VanillaGrAPE baselines + multi-probe alignment estimator + dataset / sparse-mm utilities. - experiments/: 19 runners reproducing every figure / table in the paper. - figures/: 4 generators + the 4 PDFs cited in the report. - paper/: NeurIPS .tex and consolidated experiments_master notes. Smoke test: 50-epoch Cora GCN L=4 gives BP 77.3% / KAFT 79.0%.