Replication & reproducibility
Trace published work to its sources and a useful next check.
Choose a useful starting point.
Begin with an exact published result and identify what a new contribution would test. A rerun, an independently written implementation and a changed-data extension answer different questions. Preserve the upstream authorship and version, and state the scope of your own contribution.
These external articles remain publications of their original venues. Library inclusion is not editorial acceptance or independent verification here. Inspect source permissions, unresolved inputs and the proposed comparison before deciding whether a reproduction can be bounded and useful.
Questions to work through.
Turn a published ML replication into a bounded next check
Which specific claim in an existing label-smoothing or noisy-label replication can be mapped to accessible code, data and an affordable evaluation?
Open the brief RESEARCH BRIEF · 6 SOURCESExplain a score difference before blaming the model
Do evaluation harnesses agree on the same frozen predictions once normalization, aggregation and failure handling are made explicit?
Open the briefExplore the sources.
All 246 resources →Iris
Flower measurements for a compact, interpretable multiclass baseline and leakage audit.
Hypothesis
Property-based testing tools that generate and simplify test inputs.
2D elastodynamic metamaterials
Pixelated metamaterial unit-cell designs and band-gap locations and widths for investigating simulation surrogate reliability.
3W dataset
Oil-production process signals for studying event detection across operating scenarios.
[Re] A general model of hippocampal and dorsal striatal learning and decision making
A replication of a model combining hippocampal and dorsal-striatal learning for spatial decision making.
[Re] A Multi-Functional Synthetic Gene Network
An Octave replication of a multifunctional synthetic gene-network model involving oscillatory and switching behavior.
[Re] A Neurodynamical Model for Working Memory
A replication of a neurodynamical working-memory model using recurrent or echo-state networks.
[Re] A Reservoir Computing Model of Reward-Modulated Motor Learning and Automaticity
A replication of reward-modulated motor learning and automaticity in a reservoir-computing model.
[Re] A simple rule for the evolution of cooperation on graphs and social networks
A replication about the evolution of cooperation on graphs and social networks.
[Re] Assortative matching and search
A Python replication of a search-and-matching model framed through game theory and markets.
[Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement
A replication examining lexical methods for measuring bias and sensitivity to seed choices.
[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
A replication about Thompson sampling and bandit-guided sequence optimization.