Neural CFRS is a non-autoregressive one-shot framework for CVRP that uses entropic optimal transport for capacitated clustering and achieves competitive gaps on large instances.
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RLGT is a modular reinforcement learning framework for extremal graph theory that handles undirected, directed, looped, and multi-colored graphs to facilitate future research.
Interval counterfactual explanations outperform point counterfactuals and feature importance scores in boosting model understanding and demonstrated trust according to a within-subjects user study.
RKO with tailored decoders yields competitive or superior solutions to commercial MIP solvers on constrained portfolio optimization and time-dependent TSP benchmarks.
citing papers explorer
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Neural Cluster First, Route Second: One-Shot Capacitated Vehicle Routing via Differentiable Optimal Transport
Neural CFRS is a non-autoregressive one-shot framework for CVRP that uses entropic optimal transport for capacitated clustering and achieves competitive gaps on large instances.
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RLGT: A reinforcement learning framework for extremal graph theory
RLGT is a modular reinforcement learning framework for extremal graph theory that handles undirected, directed, looped, and multi-colored graphs to facilitate future research.
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Improving understanding and trust in AI: How users benefit from interval-based counterfactual explanations
Interval counterfactual explanations outperform point counterfactuals and feature importance scores in boosting model understanding and demonstrated trust according to a within-subjects user study.
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Applying a Random-Key Optimizer on Mixed Integer Programs
RKO with tailored decoders yields competitive or superior solutions to commercial MIP solvers on constrained portfolio optimization and time-dependent TSP benchmarks.