{"total":100,"rows":[{"id":"2311.12424","title":"Looped Transformers are Better at Learning Learning Algorithms","created":"2023-11-21","cited_by_count":149,"area":null},{"id":"2103.12803","title":"JFB: Jacobian-Free Backpropagation for Implicit Networks","created":"2021-03-23","cited_by_count":86,"area":null},{"id":"2111.05177","title":"On Training Implicit Models","created":"2021-11-09","cited_by_count":75,"area":null},{"id":"2106.14342","title":"Stabilizing Equilibrium Models by Jacobian Regularization","created":"2021-06-28","cited_by_count":72,"area":null},{"id":"2203.08205","title":"Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling","created":"2022-03-15","cited_by_count":65,"area":null},{"id":"2204.08442","title":"Deep Equilibrium Optical Flow Estimation","created":"2022-04-18","cited_by_count":64,"area":null},{"id":"2401.08639","title":"One-Step Diffusion Distillation via Deep Equilibrium Models","created":"2023-12-12","cited_by_count":61,"area":"diffusion"},{"id":"2301.11526","title":"Direct Parameterization of Lipschitz-Bounded Deep Networks","created":"2023-01-27","cited_by_count":51,"area":null},{"id":"2104.05942","title":"Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness","created":"2021-04-13","cited_by_count":45,"area":null},{"id":"2201.02217","title":"Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network","created":"2022-01-06","cited_by_count":45,"area":null},{"id":"2106.04350","title":"Nonsmooth Implicit Differentiation for Machine Learning and Optimization","created":"2021-06-08","cited_by_count":43,"area":null},{"id":"2210.12867","title":"Deep Equilibrium Approaches to Diffusion Models","created":"2022-10-23","cited_by_count":42,"area":"diffusion"},{"id":"2211.09961","title":"Path Independent Equilibrium Models Can Better Exploit Test-Time Computation","created":"2022-11-18","cited_by_count":38,"area":null},{"id":"2304.00600","title":"Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models","created":"2023-04-02","cited_by_count":27,"area":null},{"id":"2205.13051","title":"Online Deep Equilibrium Learning for Regularization by Denoising","created":"2022-05-25","cited_by_count":22,"area":null},{"id":"2310.18605","title":"TorchDEQ: A Library for Deep Equilibrium Models","created":"2023-10-28","cited_by_count":21,"area":null},{"id":"2106.03194","title":"Robust Implicit Networks via Non-Euclidean Contractions","created":"2021-06-06","cited_by_count":20,"area":null},{"id":"2312.00234","title":"Deep Equilibrium Based Neural Operators for Steady-State PDEs","created":"2023-11-30","cited_by_count":19,"area":null},{"id":"2508.10480","title":"Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers","created":"2025-08-14","cited_by_count":19,"area":null},{"id":"2104.14090","title":"Feasibility-based Fixed Point Networks","created":"2021-04-29","cited_by_count":17,"area":null},{"id":"2111.13236","title":"Joint inference and input optimization in equilibrium networks","created":"2021-11-25","cited_by_count":15,"area":null},{"id":"2306.01429","title":"A Closer Look at the Adversarial Robustness of Deep Equilibrium Models","created":"2023-06-02","cited_by_count":13,"area":null},{"id":"2106.01680","title":"Convergent Graph Solvers","created":"2021-06-03","cited_by_count":12,"area":null},{"id":"2103.14867","title":"A nonlinear diffusion method for semi-supervised learning on hypergraphs","created":"2021-03-27","cited_by_count":11,"area":null},{"id":"2205.13814","title":"Global Convergence of Over-parameterized Deep Equilibrium Models","created":"2022-05-27","cited_by_count":10,"area":null},{"id":"2304.12707","title":"Lyapunov-Stable Deep Equilibrium Models","created":"2023-04-25","cited_by_count":10,"area":null},{"id":"2410.06324","title":"Differentiation Through Black-Box Quadratic Programming Solvers","created":"2024-10-08","cited_by_count":10,"area":null},{"id":"2402.01344","title":"Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks","created":"2024-02-02","cited_by_count":9,"area":null},{"id":"2112.05310","title":"Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach","created":"2021-12-10","cited_by_count":8,"area":null},{"id":"2207.09432","title":"Deep equilibrium networks are sensitive to initialization statistics","created":"2022-07-19","cited_by_count":8,"area":null},{"id":"2310.14062","title":"On the Neural Tangent Kernel of Equilibrium Models","created":"2023-10-21","cited_by_count":7,"area":null},{"id":"2402.04029","title":"Positive concave deep equilibrium models","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2410.03020","title":"On Logical Extrapolation for Mazes with Recurrent and Implicit Networks","created":"2024-10-03","cited_by_count":7,"area":null},{"id":"2508.14995","title":"Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs","created":"2025-08-20","cited_by_count":7,"area":null},{"id":"2210.08176","title":"Invertible Monotone Operators for Normalizing Flows","created":"2022-10-15","cited_by_count":6,"area":null},{"id":"2210.13542","title":"Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation","created":"2022-10-24","cited_by_count":6,"area":null},{"id":"2402.02697","title":"Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures","created":"2024-02-05","cited_by_count":6,"area":null},{"id":"2407.05920","title":"LPGD: A General Framework for Backpropagation through Embedded Optimization Layers","created":"2024-07-08","cited_by_count":6,"area":null},{"id":"2105.13228","title":"Optimization Induced Equilibrium Networks","created":"2021-05-27","cited_by_count":5,"area":null},{"id":"2112.09891","title":"Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI","created":"2021-12-18","cited_by_count":5,"area":null},{"id":"2205.07463","title":"Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths","created":"2022-05-16","cited_by_count":5,"area":null},{"id":"2212.07844","title":"Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems","created":"2022-12-15","cited_by_count":5,"area":null},{"id":"2509.12917","title":"Reversible Deep Equilibrium Models","created":"2025-09-16","cited_by_count":5,"area":null},{"id":"2111.11380","title":"Improved Model based Deep Learning using Monotone Operator Learning (MOL)","created":"2021-11-22","cited_by_count":4,"area":null},{"id":"2206.01730","title":"On the complexity of nonsmooth automatic differentiation","created":"2022-06-01","cited_by_count":4,"area":null},{"id":"2207.07475","title":"Stable Invariant Models via Koopman Spectra","created":"2022-07-15","cited_by_count":4,"area":null},{"id":"2208.03107","title":"Fixed-Point Automatic Differentiation of Forward--Backward Splitting Algorithms for Partly Smooth Functions","created":"2022-08-05","cited_by_count":4,"area":null},{"id":"2211.05943","title":"Deep equilibrium models as estimators for continuous latent variables","created":"2022-11-11","cited_by_count":4,"area":null},{"id":"2410.07427","title":"A Generalization Bound for a Family of Implicit Networks","created":"2024-10-09","cited_by_count":4,"area":null},{"id":"2503.01140","title":"DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows","created":"2025-03-03","cited_by_count":4,"area":null},{"id":"2210.16940","title":"FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs","created":"2022-10-30","cited_by_count":3,"area":null},{"id":"2303.05246","title":"Efficient Certified Training and Robustness Verification of Neural ODEs","created":"2023-03-09","cited_by_count":3,"area":null},{"id":"2304.13061","title":"iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer","created":"2023-04-25","cited_by_count":3,"area":null},{"id":"2403.00720","title":"Subhomogeneous Deep Equilibrium Models","created":"2024-03-01","cited_by_count":3,"area":null},{"id":"2410.08524","title":"IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks","created":"2024-10-11","cited_by_count":3,"area":null},{"id":"2410.23391","title":"Understanding Representation of Deep Equilibrium Models from Neural Collapse Perspective","created":"2024-10-30","cited_by_count":3,"area":null},{"id":"2603.10562","title":"Quantization Robustness of Monotone Operator Equilibrium Networks","created":"2026-03-11","cited_by_count":3,"area":null},{"id":"2607.09097","title":"Solving Stochastic Fixed-Point Equations with High Probability","created":"2026-07-10","cited_by_count":3,"area":null},{"id":"2204.12786","title":"Machines of finite depth: towards a formalization of neural networks","created":"2022-04-27","cited_by_count":2,"area":null},{"id":"2209.15562","title":"On the optimization and generalization of overparameterized implicit neural networks","created":"2022-09-30","cited_by_count":2,"area":null},{"id":"2306.01435","title":"Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2311.15673","title":"Accelerating Hopfield Network Dynamics: Beyond Synchronous Updates and Forward Euler","created":"2023-11-27","cited_by_count":2,"area":null},{"id":"2410.23940","title":"Quantum Deep Equilibrium Models","created":"2024-10-31","cited_by_count":2,"area":null},{"id":"2411.00899","title":"Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing","created":"2024-11-01","cited_by_count":2,"area":null},{"id":"2412.11301","title":"Semi-Implicit Neural Ordinary Differential Equations","created":"2024-12-15","cited_by_count":2,"area":null},{"id":"2503.17269","title":"Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models","created":"2025-03-21","cited_by_count":2,"area":null},{"id":"2504.01250","title":"R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks","created":"2025-04-01","cited_by_count":2,"area":null},{"id":"2602.03024","title":"Consistency Deep Equilibrium Models","created":"2026-02-03","cited_by_count":2,"area":null},{"id":"2603.29496","title":"Metriplector: From Field Theory to Neural Architecture","created":"2026-03-31","cited_by_count":2,"area":null},{"id":"2110.08260","title":"Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks","created":"2021-10-14","cited_by_count":1,"area":null},{"id":"2205.01080","title":"A Probabilistic Interpretation of Transformers","created":"2022-04-28","cited_by_count":1,"area":null},{"id":"2209.09389","title":"State-driven Implicit Modeling for Sparsity and Robustness in Neural Networks","created":"2022-09-19","cited_by_count":1,"area":null},{"id":"2211.10629","title":"Unifying Label-inputted Graph Neural Networks with Deep Equilibrium Models","created":"2022-11-19","cited_by_count":1,"area":null},{"id":"2410.15923","title":"Automatic Differentiation of Optimization Algorithms with Time-Varying Updates","created":"2024-10-21","cited_by_count":1,"area":null},{"id":"2412.11239","title":"Learning Set Functions with Implicit Differentiation","created":"2024-12-15","cited_by_count":1,"area":null},{"id":"2509.13793","title":"Circuit realization and hardware linearization of monotone operator equilibrium networks","created":"2025-09-17","cited_by_count":1,"area":null},{"id":"2602.03297","title":"Lipschitz Multiscale Deep Equilibrium Models: A Theoretically Guaranteed and Accelerated Approach","created":"2026-02-03","cited_by_count":1,"area":null},{"id":"2605.07277","title":"Bifurcation Models: Learning Set-Valued Solution Maps with Weight-Tied Dynamics","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2607.29158","title":"Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2608.23725","title":"Response Renormalization for Critical Deep Equilibrium Models","created":"2026-08-24","cited_by_count":1,"area":null},{"id":"2106.00906","title":"Operator Splitting for Learning to Predict Equilibria in Convex Games","created":"2021-06-02","cited_by_count":0,"area":null},{"id":"2204.13492","title":"Representation Recycling for Streaming Video Analysis","created":"2022-04-28","cited_by_count":0,"area":null},{"id":"2208.03889","title":"Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach","created":"2022-08-08","cited_by_count":0,"area":null},{"id":"2302.10895","title":"CQnet: convex-geometric interpretation and constraining neural-network trajectories","created":"2023-02-09","cited_by_count":0,"area":null},{"id":"2307.04990","title":"Monotone deep Boltzmann machines","created":"2023-07-11","cited_by_count":0,"area":null},{"id":"2307.08013","title":"Revisiting Implicit Models: Sparsity Trade-offs Capability in Weight-tied Model for Vision Tasks","created":"2023-07-16","cited_by_count":0,"area":null},{"id":"2312.07759","title":"IDKM: Memory Efficient Neural Network Quantization via Implicit, Differentiable k-Means","created":"2023-12-12","cited_by_count":0,"area":null},{"id":"2402.02065","title":"Training Implicit Networks for Image Deblurring using Jacobian-Free Backpropagation","created":"2024-02-03","cited_by_count":0,"area":null},{"id":"2507.20088","title":"Learning Latent Graph Geometry via Fixed-Point Schr\\\"odinger-Type Activation: A Theoretical Study","created":"2025-07-27","cited_by_count":0,"area":null},{"id":"2508.15553","title":"Deep Equilibrium Convolutional Sparse Coding for Hyperspectral Image Denoising","created":"2025-08-21","cited_by_count":0,"area":null},{"id":"2512.05915","title":"LDLT $\\mathcal{L}$-Lipschitz Network: Generalized Deep End-To-End Lipschitz Network Construction","created":"2025-12-05","cited_by_count":0,"area":null},{"id":"2601.17207","title":"NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations","created":"2026-01-23","cited_by_count":0,"area":null},{"id":"2604.15238","title":"A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2605.08681","title":"Core-Halo Decomposition: Decentralizing Large-Scale Fixed-Point Problems","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2606.07114","title":"DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2607.11116","title":"The Equilibrium Is the Initialization: Lazy Identity Collapse in Physics-Structured Deep Equilibrium Reasoning","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2607.18829","title":"Countercurrent Multiplier Networks: A Renal-Inspired Iterative Operator with Provably Bounded Fixed-Point Dynamics","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2607.20674","title":"End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2609.16485","title":"Certified Inference and Training for Deep Equilibrium Networks: A Continuation Framework with Polynomial Complexity Guarantees","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.39277","title":"A Tilted Bowl Is Not a Slippery Slope: Compressing Looped Models","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}