Sep 27, 2024 · We demonstrate reconstruction of a hidden network containing over 1.5 million parameters, and of one 7 layers deep, the largest and deepest reconstructions to ...

We present a novel query generation algorithm that produces maximally informative samples, letting us untangle the non-linear relationships efficiently.

Sequencing the Neurome: Towards Scalable Exact. Parameter Reconstruction of Black-Box Neural. Networks. Judah Goldfeder. Columbia University. Quinten Roets.

Oct 13, 2024 · Inferring the exact parameters of a neural network with only query access is an NP-Hard problem, with few practical existing algorithms.

Supplementary Information for Sequencing the. 1. Neurome: Towards Scalable Exact Parameter. 2. Reconstruction of Black-Box Neural Networks. 3. Judah Goldfeder1 ...

Inferring the exact parameters of a neural network with only query access is an NP-Hard problem, with few practical existing algorithms.

Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction of Black-Box Neural Networks · no code implementations • 27 Sep 2024 • Judah Goldfeder ...

Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction of Black-Box Neural Networks · Computer Science, Biology · 2024.

Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction of Black-Box Neural Networks ... Abstract:Inferring the exact parameters of a neural ...

Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks · Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction of Black-Box ...