Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows | Paper Citation Record

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This paper cites Score-based generative modeling through stochastic differ- ential equations,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Score-based generative modeling through stochastic differ- ential equations,

Reference 1

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This paper cites Diffusion models beat gans on image synthesis,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Diffusion models beat gans on image synthesis,

Reference 2

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Classifier-free diffusion guidance,

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This paper cites Flow matching for generative modeling,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Flow matching for generative modeling,

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This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Flow straight and fast: Learning to generate and transfer data with rectified flow,

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This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 6

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This paper cites Cfg-zero*: Improved classifier-free guidance for flow matching models,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Cfg-zero*: Improved classifier-free guidance for flow matching models,

Reference 7

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This paper cites On the guidance of flow matching,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows On the guidance of flow matching,

Reference 8

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This paper cites Generalized protein pocket generation with prior-informed flow matching,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Generalized protein pocket generation with prior-informed flow matching,

Reference 9

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This paper cites Planning with diffusion for flexible behavior synthesis,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Planning with diffusion for flexible behavior synthesis,

Reference 10

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This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 11

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This paper cites Denoising diffusion restoration models,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Denoising diffusion restoration models,

Reference 12

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This paper cites Diffusion posterior sampling for general noisy inverse problems,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Diffusion posterior sampling for general noisy inverse problems,

Reference 13

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This paper cites Nonlinear systems third edition,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Nonlinear systems third edition,

Reference 14

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Unresolved cited work

Reference 15

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This paper cites Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview,

Reference 16

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This paper cites Neural lyapunov control,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Neural lyapunov control,

Reference 17

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Neural stochastic control,

Reference 18

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This paper cites Neural Event-Triggered Control with Optimal Scheduling.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Neural Event-Triggered Control with Optimal Scheduling

Reference 19

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This paper cites Sync: Safety-aware neural control for stabilizing stochastic delay-differential equations,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Sync: Safety-aware neural control for stabilizing stochastic delay-differential equations,

Reference 20

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This paper cites Learning safe multi-agent control with decentralized neural barrier certificates,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Learning safe multi-agent control with decentralized neural barrier certificates,

Reference 21

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This paper cites Learning certified control using contraction metric,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Learning certified control using contraction metric,

Reference 22

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This paper cites Stabilization with relaxed controls,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Stabilization with relaxed controls,

Reference 23

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This paper cites A ‘universal’construction of artstein’s theorem on nonlin- ear stabilization,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows A ‘universal’construction of artstein’s theorem on nonlin- ear stabilization,

Reference 24

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This paper cites Nonlinear feedback design for fixed-time stabilization of linear control systems,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Nonlinear feedback design for fixed-time stabilization of linear control systems,

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This paper cites Calibrated multi-preference optimization for align- ing diffusion models,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Calibrated multi-preference optimization for align- ing diffusion models,

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This paper cites Training diffu- sion models with reinforcement learning,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Training diffu- sion models with reinforcement learning,

Reference 27

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This paper cites Towards Controllable Diffusion Models via Reward-Guided Exploration.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Towards Controllable Diffusion Models via Reward-Guided Exploration

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This paper cites A tutorial on energy-based learning,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows A tutorial on energy-based learning,

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This paper cites Incorporating stability into flow matching,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Incorporating stability into flow matching,

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This paper cites Stochastic interpolant: A new framework for generative modeling,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Stochastic interpolant: A new framework for generative modeling,

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This paper cites Generative modeling with phase stochas- tic bridges,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Generative modeling with phase stochas- tic bridges,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Generative modeling by estimating gradients of the data distribution,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Implicit generation and modeling with energy based models,

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This paper cites Physics-informed neural network lyapunov functions: Pde characterization, learning, and verification,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Physics-informed neural network lyapunov functions: Pde characterization, learning, and verification,

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This paper cites Stable neural ode with lyapunov-stable equilibrium points for defending against adversarial attacks,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Stable neural ode with lyapunov-stable equilibrium points for defending against adversarial attacks,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Zero-shot image restoration using denoising diffusion null-space model,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Pseudoinverse-guided diffusion models for inverse problems,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Training-free Linear Image Inverses via Flows

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Flow priors for linear inverse problems via iterative corrupted trajectory matching,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Pnp-flow: Plug- and-play image restoration with flow matching,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Fig: Flow with interpolant guidance for linear inverse problems,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Film: Visual reasoning with a general conditioning layer,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Learning multiple visual domains with residual adapters,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Efficient parametrization of multi-domain deep neural networks,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Model-agnostic meta-learning for fast adaptation of deep networks,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Meta-learning with latent embedding optimization,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Parameter-efficient transfer learning for nlp,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Wiener,Cybernetics or Control and Communication in the Animal and the Machine

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Mao,Stochastic differential equations and applications

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This paper cites Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Projection-based integrators for improved motion control: Formalization, well-posedness and stability of hybrid integrator- gain systems,

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This paper cites Lyapunov-based Safe Policy Optimization for Continuous Control.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Lyapunov-based Safe Policy Optimization for Continuous Control

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Fessnc: Fast exponentially sta- ble and safe neural controller,

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This paper cites Contrastive energy prediction for exact energy-guided diffusion sampling in offline rein- forcement learning,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Contrastive energy prediction for exact energy-guided diffusion sampling in offline rein- forcement learning,

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows D4RL: Datasets for Deep Data-Driven Reinforcement Learning

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Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Flow matching on general geometries,

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This paper cites Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

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This paper cites Energy matching: Unifying flow matching and energy-based models for generative mod- eling,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Energy matching: Unifying flow matching and energy-based models for generative mod- eling,

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This paper cites Finite-time and fixed-time stabilization: Implicit lyapunov function approach,.

Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows Finite-time and fixed-time stabilization: Implicit lyapunov function approach,

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