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https://deepai.org/publication/efficient-bayesian-inference-using-physics-informed-invertible-neural-networks-for-inverse-problems Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems... Apr 25, 2023 - 04/25/23 - In the paper, we propose a novel approach for solving Bayesian inverse problems with physics-informed invertible neural networks (... bayesian inference https://arxiv.org/abs/1509.08755 [1509.08755] Transmitting-state invertible cellular automata Abstract page for arXiv paper 1509.08755: Transmitting-state invertible cellular automata 1509 08755 transmitting state invertible https://arxiv.org/abs/2006.10137v1 [2006.10137v1] MoFlow: An Invertible Flow Model for Generating Molecular Graphs Abstract page for arXiv paper 2006.10137v1: MoFlow: An Invertible Flow Model for Generating Molecular Graphs 2006 invertible https://deepai.org/publication/jeopardy-an-invertible-functional-programming-language Jeopardy: An Invertible Functional Programming Language | DeepAI Sep 6, 2022 - 09/06/22 - Algorithms are ways of mapping problems to solutions. An algorithm is invertible precisely when this mapping is injective, such th... functional programming jeopardy invertible language deepai https://arxiv.org/abs/2211.16507 [2211.16507] Structure-Preserving Invariant Interpolation Schemes for Invertible Second-Order... Abstract page for arXiv paper 2211.16507: Structure-Preserving Invariant Interpolation Schemes for Invertible Second-Order Tensors 2211 16507 structure preserving invariant https://deepai.org/publication/generative-flow-via-invertible-nxn-convolution Generative Flow via Invertible nxn Convolution | DeepAI May 24, 2019 - 05/24/19 - Flow-based generative models have recently become one of the most efficient approaches to model the data generation. Indeed, they ... generative flow via invertible nxn https://arxiv.org/abs/2509.03910 [2509.03910] An invertible generative model for forward and inverse problems Abstract page for arXiv paper 2509.03910: An invertible generative model for forward and inverse problems generative model 2509 03910 invertible https://arxiv.org/abs/2209.02772?context=cs.LG [2209.02772] Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems Abstract page for arXiv paper 2209.02772: Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems neural operators 2209 02772 semi supervised https://aclanthology.org/2024.acl-long.116/ Learning Disentangled Semantic Spaces of Explanations via Invertible Neural Networks - ACL Anthology Yingji Zhang, Danilo Carvalho, Andre Freitas. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).... semantic spaces https://www.preprints.org/manuscript/202505.2413 The Structural Closure Property of Linear Time-Invariant Invertible Systems[v1] | Preprints.org This paper introduces and proves a novel proposition on the structural closure property of Linear Time-Invariant (LTI) invertible systems. Specifically, it... linear time invariant https://openreview.net/forum?id=6VpeS27viTq Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations |... Owing much to the revolution of information technology, recent progress of deep learning benefits incredibly from the vastly enhanced access to data available... learnability lock authorized control adversarial https://github.com/openai/glow GitHub - openai/glow: Code for reproducing results in "Glow: Generative Flow with Invertible 1x1... Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions" - openai/glow https://arxiv.org/abs/1101.2245 [1101.2245] Invertible Bloom Lookup Tables Abstract page for arXiv paper 1101.2245: Invertible Bloom Lookup Tables 1101 2245 invertible bloom lookup https://www.scirp.org/journal/paperinformation?paperid=75358 Alternative Infinitesimal Generator of Invertible Evolution Families Explore the logarithm representation of evolution operators and the characterization of invertible evolution families. Discover the concept of evolution... infinitesimal generator alternative invertible evolution families https://openreview.net/forum?id=HJsjkMb0Z i-RevNet: Deep Invertible Networks | OpenReview It is widely believed that the success of deep convolutional networks is based on progressively discarding uninformative variability about the input with... deep invertible networks openreview https://openreview.net/forum?id=_J27aSSip5m&referrer=%5Bthe%20profile%20of%20Yang%20Li%5D(%2Fprofile%3Fid%3D~Yang_Li46) InvVis: Large-Scale Data Embedding for Invertible Visualization | OpenReview We present InvVis, a new approach for invertible visualization, which is reconstructing or further modifying a visualization from an image. InvVis allows the... large scale data embedding invertible visualization https://deepai.org/publication/neural-parts-learning-expressive-3d-shape-abstractions-with-invertible-neural-networks Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks | DeepAI Mar 18, 2021 - 03/18/21 - Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parall... 3d shape neural parts learning expressive https://www.osti.gov/pages/biblio/2500907-non-invertible-symmetries-finite-group-gauge-theory Non-invertible symmetries in finite-group gauge theory (Journal Article) | OSTI.GOV The U.S. Department of Energy's Office of Scientific and Technical Information finite group https://openreview.net/forum?id=o6ukhJLzMQ Augmented Invertible Koopman Autoencoder for long-term time series forecasting | OpenReview Following the introduction of Dynamic Mode Decomposition and its numerous extensions, many neural autoencoder-based implementations of the Koopman operator... time series forecasting long term augmented invertible koopman https://ojp.gov/media/document/227071 Theory of Invertible and Injective Deep Neural Networks for Likelihood Estimation and Uncertainty... deep neural networks theory of https://arxiv.org/abs/2211.01618 [2211.01618] Self Supervised Low Dose Computed Tomography Image Denoising Using Invertible Network... Abstract page for arXiv paper 2211.01618: Self Supervised Low Dose Computed Tomography Image Denoising Using Invertible Network Exploiting Inter Slice... https://openreview.net/forum?id=txpYITR8oa AmbientFlow: Invertible generative models from incomplete, noisy measurements | OpenReview Generative models have gained popularity for their potential applications in imaging science, such as image reconstruction, posterior sampling and data... generative models invertible incomplete noisy measurements https://openreview.net/forum?id=Vcu755vOXZ&referrer=%5Bthe%20profile%20of%20Ralf%20Mikut%5D(%2Fprofile%3Fid%3D~Ralf_Mikut1) Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible... In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, many existing... a conditional generating probabilistic forecasts arbitrary https://deepai.org/publication/deep-invertible-approximation-of-topologically-rich-maps-between-manifolds Deep Invertible Approximation of Topologically Rich Maps between Manifolds | DeepAI Oct 2, 2022 - 10/02/22 - How can we design neural networks that allow for stable universal approximation of maps between topologically interesting manifold... deep invertible approximation topologically rich https://www.mapleprimes.com/questions/211872-Generate-Invertible-4x4-Matrices-Over-F2- Generate invertible 4x4 matrices over F_2 - MaplePrimes f 2 generate invertible 4x4 matrices https://www.varsitytutors.com/practice/subjects/algebra-ii/help/restrict-domain-to-make-invertible Restrict Domain to Make Invertible -... | Varsity Tutors Get help with Restrict Domain to Make Invertible in Algebra 2. Get detailed explanations, step-by-step solutions, and instant feedback to improve your... to make restrict domain invertible varsity https://openreview.net/forum?id=B3VR4dIy9e AmbientFlow: Invertible generative models from incomplete, noisy imaging measurements | OpenReview Generative models, including normalizing flows, are gaining popularity in imaging science for tasks such as image reconstruction, posterior sampling, and data... generative models invertible incomplete noisy imaging https://www.ojp.gov/library/publications/theory-invertible-and-injective-deep-neural-networks-likelihood-estimation-and Theory of Invertible and Injective Deep Neural Networks for Likelihood Estimation and Uncertainty... The author presents a theory of invertible and injective deep neural networks for likelihood estimation and uncertainty quantification. deep neural networks theory of https://deepai.org/publication/discrete-flows-invertible-generative-models-of-discrete-data Discrete Flows: Invertible Generative Models of Discrete Data | DeepAI May 24, 2019 - 05/24/19 - While normalizing flows have led to significant advances in modeling high-dimensional continuous distributions, their applicabilit... generative models discrete flows invertible data https://openreview.net/forum?id=DhgpsRWHl4Z Invertible Learned Primal-Dual | OpenReview We propose an invertible Learned Primal-Dual architecture for 3D reconstruction in computed tomography. primal dual invertible learned openreview https://www.stir.ac.uk/research/hub/publication/1696624 Article | Preference Conditions for Invertible Demand Functions | University of Stirling university of article preference conditions invertible https://openreview.net/forum?id=ILmND4b1BK Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems | OpenReview Fourier Neural Operator (FNO) is a powerful and popular operator learning method. However, FNO is mainly used in forward prediction, yet a great many... neural operators https://www.mdpi.com/2073-4360/15/8/1884 Process Parameter Prediction for Fused Deposition Modeling Using Invertible Neural Networks Additive manufacturing has revolutionized prototyping and small-scale production in the past years. By creating parts layer by layer, a tool-less production... fused deposition modeling process parameter prediction https://www.mdpi.com/2072-4292/13/2/295 A Task-Driven Invertible Projection Matrix Learning Algorithm for Hyperspectral Compressed Sensing The high complexity of the reconstruction algorithm is the main bottleneck of the hyperspectral image (HSI) compression technology based on compressed sensing.... projection matrix