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Found 4 papers, 2 papers with code
A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions
In this paper, we build on prior work and propose a novel framework for reverse engineering of deceptions which supposes that the clean data lies in the range of a GAN.
Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees
We pose this problem as a block-sparse recovery problem, where both the signal and the attack are assumed to lie in a union of subspaces that includes one subspace per class and one subspace per attack type.
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning
Furthermore, to approximate solutions to constrained combinatorial optimization problems such as the TSP with time windows, we train hierarchical GPNs (HGPNs) using RL, which learns a hierarchical policy to find an optimal city permutation under constraints.
Ranked #2 on
Traveling Salesman Problem
on TSPLIB
Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations
Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.
