- [] Conjugate Gradient
- [] GMRES
- [] Type-I/II Anderson
- [] Broyden class
- [] HyperSolver
- [] SHINE
- SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
- [] monDEQ
- Monotone operator equilibrium networks
- [] DE-Prox
- Deep Equilibrium Architectures for Inverse Problems in Imaging
- [] JIIO
- Joint inference and input optimization in equilibrium networks
- [] EIGNN
- EIGNN: Efficient Infinite-Depth Graph Neural Networks
- [] MOptEq
- Optimization inspired Multi-Branch Equilibrium Models
- [] GIND
- Optimization-Induced Graph Implicit Nonlinear Diffusion
- [] Adversarial Defense
- A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
- [] MGNNI
- MGNNI: Multiscale Graph Neural Networks with Implicit Layers
- [] Path Independence
- Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
- [] NERD
- Equilibrium Image Denoising With Implicit Differentiation
- [] Entropy Reduction
- Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics
- [] DEQNAR
- Deep Equilibrium Non-Autoregressive Sequence Learning
- [] LDEQ
- Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models
- [] DEQDet
- Deep Equilibrium Object Detection
- [] FNO-DEQ
- Deep Equilibrium Based Neural Operators for Steady-State PDEs
- [] GET
- One-Step Diffusion Distillation via Deep Equilibrium Models
To be continues.