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Found 6 papers, 4 papers with code
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation
The field of tropical algebra is closely linked with the domain of neural networks with piecewise linear activations, since their output can be described via tropical polynomials in the max-plus semiring.
Language models scale reliably with over-training and on downstream tasks
We fit scaling laws that extrapolate in both the number of model parameters and the ratio of training tokens to parameters.
DataComp: In search of the next generation of multimodal datasets
Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms.
Inverse Problems Leveraging Pre-trained Contrastive Representations
The problem is to recover the representation of an image R(x), if we are only given a corrupted version A(x), for some known forward operator A.
Tropical Geometrical Zonotope Reduction as Applied to Neural Network Compression.
Based on this result, we propose geometrical neural network compression methods that employ the K-means algorithm.
Tropical Polynomial Division and Neural Networks
In this work, we examine the process of Tropical Polynomial Division, a geometric method which seeks to emulate the division of regular polynomials, when applied to those of the max-plus semiring.
