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Found 7 papers, 5 papers with code
NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment
However, building efficient tools to perform alignment can be challenging, especially for the largest and most competent LLMs which often contain tens or hundreds of billions of parameters.
Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching
Cross-device user matching is a critical problem in numerous domains, including advertising, recommender systems, and cybersecurity.
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Domain decomposition methods (DDMs) are popular solvers for discretized systems of partial differential equations (PDEs), with one-level and multilevel variants.
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation
Sparse matrix representations are ubiquitous in computational science and machine learning, leading to significant reductions in compute time, in comparison to dense representation, for problems that have local connectivity.
Learning Interface Conditions in Domain Decomposition Solvers
Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations.
Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning
A system of linear equations defines a graph on the set of unknowns and each level of a multigrid solver requires the selection of an appropriate coarse graph along with restriction and interpolation operators that map to and from the coarse representation.
Local Navigation and Docking of an Autonomous Robot Mower using Reinforcement Learning and Computer Vision
We demonstrate a successful navigation and docking control system for the John Deere Tango autonomous mower, using only a single camera as the input.
