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Found 7 papers, 5 papers with code
Discrete Denoising Diffusion Approach to Integer Factorization
Integer factorization is a famous computational problem unknown whether being solvable in the polynomial time.
Denoising Diffusion for Sampling SAT Solutions
Generating diverse solutions to the Boolean Satisfiability Problem (SAT) is a hard computational problem with practical applications for testing and functional verification of software and hardware designs.
Gates Are Not What You Need in RNNs
In this paper, we propose a new recurrent cell called Residual Recurrent Unit (RRU) which beats traditional cells and does not employ a single gate.
Goal-Aware Neural SAT Solver
To demonstrate the capabilities of the query mechanism, we formulate an unsupervised (not depending on labels) loss function for Boolean Satisfiability Problem (SAT) and theoretically show that it allows the network to extract rich information about the problem.
Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time
A key requirement in sequence to sequence processing is the modeling of long range dependencies.
A Statistical Method for Object Counting
In this paper we present a new object counting method that is intended for counting similarly sized and mostly round objects.
Improving the Neural GPU Architecture for Algorithm Learning
Algorithm learning is a core problem in artificial intelligence with significant implications on automation level that can be achieved by machines.
