Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
Authors: Moritz Stargalla, Christoph Hertrich, Daniel Reichman
NeurIPS 2025 | Venue PDF | LLM Run Details | Input Tokens: 19,462 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 2,761 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our paper is of theoretical nature and we strive towards a thorough understanding of the problem of counting regions from a computational complexity perspective. |
| Researcher Affiliation | Academia | Moritz Stargalla University of Technology Nuremberg EMAIL Christoph Hertrich University of Technology Nuremberg EMAIL Daniel Reichman Worcester Polytechnic Institute EMAIL |
| Pseudocode | Yes | Algorithm 1 SEARCHAFFINEPIECE Input: A Re LU network N and a vector (a1, . . . , an, b) Qn+1. Output: 1 if Pn i=1 aixi + b is a function of an affine region of N, else 0. 1: for a {0, 1}s(N) do 2: if dim Sa = n then (Lemma A.5) 3: if Pn i=1 aixi + b = f a N(x) then return 1 (Lemma A.4) return 0 Algorithm 2 EXHAUSTIVESEARCH Input: A Re LU network N. Output: Number of affine regions of N. 1: nmax = max{n0, n1, . . . , nd+1} 2: U = 236d2n2 max Amax (Lemma A.3) 3: R = 0 4: for (a, b) { U, . . . , U}n+1 {1, . . . , U}n+1 do 5: if gcd(ai, bi) = 1 for i [n + 1] then 6: R R + SEARCHAFFINEPIECE(N, ( a1 b1 , . . . , an+1 bn+1 )) (Lemma B.4) return R |
| Open Source Code | No | Justification: No experiments. |
| Open Datasets | No | Justification: No experiments. |
| Dataset Splits | No | Justification: No experiments. |
| Hardware Specification | No | Justification: No experiments. |
| Software Dependencies | No | Justification: No experiments. |
| Experiment Setup | No | Justification: No experiments. |