The following pages link to extracted from (P1689):
Displaying 50 items.
- Neural Stochastic Contraction Metrics for Learning-based Control and Estimation (Q6353113) (← links)
- Efficient quantum algorithm for dissipative nonlinear differential equations (Q6353117) (← links)
- Optimal Resource and Demand Redistribution for Healthcare Systems Under Stress from COVID-19 (Q6353170) (← links)
- Pathwise Conditioning of Gaussian Processes (Q6353247) (← links)
- GPU Accelerated Convex Approximations for Fast Multi-Agent Trajectory Optimization (Q6353285) (← links)
- Solving Inverse Problems With Deep Neural Networks -- Robustness Included? (Q6353287) (← links)
- Modeling and Optimizing Resource Allocation Decisions through Multi-model Markov Decision Processes with Capacity Constraints (Q6353306) (← links)
- Exterior-point Optimization for Sparse and Low-rank Optimization (Q6353338) (← links)
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (Q6353342) (← links)
- Approximately Exact Line Search (Q6353358) (← links)
- Estimating Total Correlation with Mutual Information Estimators (Q6353370) (← links)
- Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment (Q6353375) (← links)
- Towards a Better Global Loss Landscape of GANs (Q6353402) (← links)
- Correlated Age-of-Information Bandits (Q6353417) (← links)
- A Distributionally Robust Optimization Approach for Unit Commitment in Microgrids (Q6353453) (← links)
- Learning ODE Models with Qualitative Structure Using Gaussian Processes (Q6353459) (← links)
- Influencing dynamics on social networks without knowledge of network microstructure (Q6353519) (← links)
- Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers (Q6353556) (← links)
- Recoverable Robust Single Machine Scheduling with Polyhedral Uncertainty (Q6353582) (← links)
- tvopt: A Python Framework for Time-Varying Optimization (Q6353710) (← links)
- FedRec: Federated Learning of Universal Receivers over Fading Channels (Q6353730) (← links)
- GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability (Q6353752) (← links)
- Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee (Q6353756) (← links)
- Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment (Q6353820) (← links)
- A simple technique for unstructured mesh generation via adaptive finite elements (Q6353834) (← links)
- Combating the Instability of Mutual Information-based Losses via Regularization (Q6353838) (← links)
- DLBFoam: An open-source dynamic load balancing model for fast reacting flow simulations in OpenFOAM (Q6353844) (← links)
- Mixing ADAM and SGD: a Combined Optimization Method (Q6353849) (← links)
- Enforcing robust control guarantees within neural network policies (Q6353860) (← links)
- Federated Composite Optimization (Q6353923) (← links)
- An Evaluation of novel method of Ill-Posed Problem for the Black-Scholes Equation solution (Q6354012) (← links)
- Hyperbolic generalized triangle groups, property (T) and finite simple quotients (Q6354026) (← links)
- Gradient Starvation: A Learning Proclivity in Neural Networks (Q6354054) (← links)
- Learning Approximate Forward Reachable Sets Using Separating Kernels (Q6354088) (← links)
- Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface (Q6354111) (← links)
- Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing (Q6354116) (← links)
- GL-Coarsener: A Graph representation learning framework to construct coarse grid hierarchy for AMG solvers (Q6354136) (← links)
- Improved rates for prediction and identification of partially observed linear dynamical systems (Q6354139) (← links)
- Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach (Q6354178) (← links)
- Continuous Blackjack: Equilibrium, Deviation and Adaptive Strategy (Q6354183) (← links)
- Distributed Power Flow and Distributed Optimization -- Formulation, Solution, and Open Source Implementation (Q6354184) (← links)
- How network properties and epidemic parameters influence stochastic SIR dynamics on scale-free random networks (Q6354219) (← links)
- SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions (Q6354221) (← links)
- On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization (Q6354226) (← links)
- Data-Driven System Level Synthesis (Q6354229) (← links)
- Distributed algorithms to determine eigenvectors of matrices on spatially distributed networks (Q6354314) (← links)
- Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations (Q6354344) (← links)
- An end-to-end data-driven optimisation framework for constrained trajectories (Q6354402) (← links)
- ADCME: Learning Spatially-varying Physical Fields using Deep Neural Networks (Q6354423) (← links)
- Wyner-Ziv Estimators for Distributed Mean Estimation with Side Information and Optimization (Q6354454) (← links)
