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https://openreview.net/forum?id=HkxF5RgC- Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip | OpenReview Combining network pruning and persistent kernels into a practical, fast, and accurate network implementation. recurrent networks sparse persistent rnns squeezing https://deepai.org/publication/on-fast-dropout-and-its-applicability-to-recurrent-networks On Fast Dropout and its Applicability to Recurrent Networks | DeepAI Nov 4, 2013 - 11/04/13 - Recurrent Neural Networks (RNNs) are rich models for the processing of sequential data. Recent work on advancing the state of the ... recurrent networks fast dropout applicability deepai https://deepai.org/publication/constrained-convolutional-recurrent-networks-to-improve-speech-quality-with-low-impact-on-recognition-accuracy Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on... Feb 16, 2018 - 02/16/18 - For a speech-enhancement algorithm, it is highly desirable to simultaneously improve perceptual quality and recognition rate. Than... recurrent networks https://openreview.net/forum?id=ZuMgYX1irC Combining Graph and Recurrent Networks for Efficient and Effective Segment Tagging | OpenReview Extremely light entity tagging model combining Transformers for text feature extraction, and Graph Neural Networks and recurrent layers for segments interaction recurrent networks combining graph https://deepai.org/publication/overcoming-the-vanishing-gradient-problem-in-plain-recurrent-networks Overcoming the vanishing gradient problem in plain recurrent networks | DeepAI Jan 18, 2018 - 01/18/18 - Plain recurrent networks greatly suffer from the vanishing gradient problem while Gated Neural Networks (GNNs) such as Long-short ... vanishing gradient problem recurrent networks overcoming plain deepai https://openreview.net/forum?id=HJ3d2Ax0- Benefits of Depth for Long-Term Memory of Recurrent Networks | OpenReview We propose a measure of long-term memory and prove that deep recurrent networks are much better fit to model long-term temporal dependencies than shallow ones. long term memory benefits of recurrent networks depth openreview https://openreview.net/forum?id=dkHfV3wB2l Recurrent networks, hidden states and beliefs in partially observable environments | OpenReview Reinforcement learning aims to learn optimal policies from interaction with environments whose dynamics are unknown. Many methods rely on the approximation of... recurrent networks partially observable hidden states https://elifesciences.org/articles/43299v1 Local online learning in recurrent networks with random feedback | eLife local online recurrent networks learning random feedback https://openreview.net/forum?id=BJpv46DGNl_ Category-orthogonal object features guide information processing in recurrent neural networks... In RNNs, category-orthogonal information (location, scale, etc. of the object) is conveyed through recurrent connectivity and is used to optimise category... features guide information processing category orthogonal object https://openreview.net/forum?id=r1gNni0qtm Generalized Tensor Models for Recurrent Neural Networks | OpenReview Analysis of expressivity and generality of recurrent neural networks with ReLu nonlinearities using Tensor-Train decomposition. recurrent neural networks generalized tensor models openreview https://openreview.net/forum?id=rJEgeXFex Predicting Medications from Diagnostic Codes with Recurrent Neural Networks | OpenReview Applying recurrent neural networks to fix errors and omissions in patient medication records. recurrent neural networks diagnostic codes predicting medications openreview https://arxiv.org/abs/2405.21064v1 [2405.21064v1] Recurrent neural networks: vanishing and exploding gradients are not the end of the... Abstract page for arXiv paper 2405.21064v1: Recurrent neural networks: vanishing and exploding gradients are not the end of the story https://jmlr.org/papers/v23/21-0368.html Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks optimization theory continuous time approximation https://deepai.org/publication/automation-of-processor-verification-using-recurrent-neural-networks Automation of Processor Verification Using Recurrent Neural Networks | DeepAI Mar 6, 2018 - 03/06/18 - When considering simulation-based verification of processors, the current trend is to generate stimuli using pseudorandom generato... recurrent neural networks automation processor verification using https://aclanthology.org/2022.emnlp-main.431/ ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks - ACL... Kai Xiong, Xiao Ding, Zhongyang Li, Li Du, Ting Liu, Bing Qin, Yi Zheng, Baoxing Huai. Proceedings of the 2022 Conference on Empirical Methods in Natural... recurrent neural networks causal chain reco reliable reasoning https://openreview.net/forum?id=xVI8g50Qfk Error Forcing in Recurrent Neural Networks | OpenReview How should feedback influence recurrent neural network (RNN) learning? One way to address the known limitations of backpropagation through time is to directly... recurrent neural networks error forcing openreview https://wandb.ai/wandb_fc/wb-tutorials/reports/Tutorial-Recurrent-Neural-Networks--Vmlldzo0NTIxMjI2 Tutorial: Recurrent Neural Networks May 31, 2023 - In this tutorial we introduce RNNs (Recurrent Neural Network) that can classify sequences of data and time series, and build one for predicting the weather. tutorial recurrent neural networks https://jmlr.org/papers/v26/24-1953.html On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes recurrent neural networks asymptotic theory https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1424184 Arrival Time Predictions for Buses using Recurrent Neural Networks DiVA portal is a finding tool for research publications and student theses written at the following universities and research institutions. arrival time predictions buses using recurrent https://arxiv.org/abs/2108.01192 [2108.01192] MOHAQ: Multi-Objective Hardware-Aware Quantization of Recurrent Neural Networks Abstract page for arXiv paper 2108.01192: MOHAQ: Multi-Objective Hardware-Aware Quantization of Recurrent Neural Networks https://arxiv.org/abs/2009.08889 [2009.08889] Large Deviations Approach to Random Recurrent Neuronal Networks: Parameter Inference... Abstract page for arXiv paper 2009.08889: Large Deviations Approach to Random Recurrent Neuronal Networks: Parameter Inference and Fluctuation-Induced... large deviations https://deepai.org/publication/delta-networks-for-optimized-recurrent-network-computation Delta Networks for Optimized Recurrent Network Computation | DeepAI Dec 16, 2016 - 12/16/16 - Many neural networks exhibit stability in their activation patterns over time in response to inputs from sensors operating under r... delta networks optimized recurrent computation https://openreview.net/forum?id=r1SnX5xCb Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks | OpenReview For every prediction we might wish to make, we must decide what to observe (what source of information) and when to observe it. Because making observations is... recurrent neural networks multi directional deep sensing active https://www.osti.gov/biblio/1649632 On the Effectiveness of Recurrent Neural Networks for Live Modeling of Cyber-Physical Systems... Attention to cyber security of cyber-physical systems (CPS) has led to the development of innovative cyber-resilient methodologies to ensure early detection... recurrent neural networks https://wandb.ai/byyoung3/ml-news/reports/SUPRA-Uptraining-Transformers-to-Recurrent-Neural-Networks-for-Efficient-Inference--Vmlldzo3OTkxNTA1 SUPRA: Uptraining Transformers to Recurrent Neural Networks for Efficient Inference recurrent neural networks supra transformers efficient inference https://elifesciences.org/reviewed-preprints/103660/reviews Neural dynamics of reversal learning in the prefrontal cortex and recurrent neural networks neural dynamics in the https://openreview.net/forum?id=LDuzgy4iOXr Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation |... A recurrent module is proposed to improve feature learning by reusing information from all previous layers in CNNs. convolutional neural networks recurrence along depth deep https://arxiv.org/abs/2101.01385 [2101.01385] Recurrent Neural Networks for Stochastic Control Problems with Delay Abstract page for arXiv paper 2101.01385: Recurrent Neural Networks for Stochastic Control Problems with Delay recurrent neural networks stochastic control 2101 01385 https://elifesciences.org/articles/71263/figures Figures and data in Nonlinear transient amplification in recurrent neural networks with short-term... The interplay of recurrent excitation and short-term plasticity enables nonlinear transient amplification, an ideal mechanism for selective amplification,... recurrent neural networks https://docs.google.com/presentation/d/1-Y3rc-Y1jryat7kkzpZStoprk2dc4fVnpmezkAcrv-c/pub?start=false&loop=false&delayms=10000&slide=id.g742e3e7cd_1_16 Recurrent Neural Networks - Google Slides Recurrent Neural Networks Rajat Shah (Team #18) recurrent neural networks google slides https://elifesciences.org/articles/108237v1/figures Figures and data in Adjoint propagation of error signal through modular recurrent neural networks... https://openreview.net/forum?id=GGIA1p9fDT CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics |... Advances in optical and electrophysiological recording technologies have made it possible to record the dynamics of thousands of neurons, opening up new... recurrent neural networks convex optimization https://arxiv.org/abs/1903.00906 [1903.00906] Understanding Feature Selection and Feature Memorization in Recurrent Neural Networks Abstract page for arXiv paper 1903.00906: Understanding Feature Selection and Feature Memorization in Recurrent Neural Networks feature selection 1903 00906 understanding https://openreview.net/forum?id=B1l6qiR5F7 Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks | OpenReview We introduce a new inductive bias that integrates tree structures in recurrent neural networks. recurrent neural networks ordered neurons integrating tree https://arxiv.org/abs/2412.06631v1 [2412.06631v1] Recurrent convolutional neural networks for non-adiabatic dynamics of... Abstract page for arXiv paper 2412.06631v1: Recurrent convolutional neural networks for non-adiabatic dynamics of quantum-classical systems convolutional neural networks 2412 recurrent https://www.pluralsight.com/resources/blog/guides/text-generation-using-recurrent-neural-networks Text Generation Using Recurrent Neural Networks | Pluralsight recurrent neural networks text generation using pluralsight https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1412559/full Frontiers | Composing recurrent spiking neural networks using locally-recurrent motifs and... In neural circuits, recurrent connectivity plays a crucial role in network function and stability.However, existing recurrent spiking neural networks (RSNNs)... spiking neural networks frontiers composing recurrent using https://www.coursera.org/courses?query=recurrent%20neural%20networks%20(rnns) Top Recurrent Neural Networks (rnns) Courses - Learn Recurrent Neural Networks (rnns) Online Recurrent Neural Networks (rnns) courses from top universities and industry leaders. Learn Recurrent Neural Networks (rnns) online with courses like... recurrent neural networks top rnns courses learn https://openreview.net/forum?id=xOK40an4ag1 Operative dimensions in unconstrained connectivity of recurrent neural networks | OpenReview We define operative dimensions in RNN weight matrices, and show that they enable us to identify a low-dimensional subspace in recurrent weight matrices which... recurrent neural networks operative dimensions connectivity openreview https://openreview.net/forum?id=H1zeHnA9KX Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks |... Finite Automata Can be Linearly decoded from Language-Recognizing RNNs using low coarseness abstraction functions and high accuracy decoders. formal languages https://www.codecademy.com/resources/docs/ai/neural-networks/recurrent-neural-networks AI | Neural Networks | Recurrent Neural Networks | Codecademy Recurrent Neural Networks are a type of neural network distinguished by storing and re-using the output from previous steps as an additional input in the... ai neural networks recurrent codecademy https://www.analyticsvidhya.com/blog/2022/04/recurrent-neural-networks-digging-a-bit-deeper/ Recurrent Neural Networks: Digging a bit deeper Apr 5, 2022 - In this article we will dig a bit deeper into Recurrent Neural Networks, we will see the mathematical details and understand it simply recurrent neural networks digging bit deeper https://elifesciences.org/articles/71263v1 Nonlinear transient amplification in recurrent neural networks with short-term plasticity | eLife recurrent neural networks https://openreview.net/forum?id=30o4ARmfC3 Evolving Connectivity for Recurrent Spiking Neural Networks | OpenReview Recurrent spiking neural networks (RSNNs) hold great potential for advancing artificial general intelligence, as they draw inspiration from the biological... spiking neural networks evolving connectivity recurrent openreview https://deepai.org/publication/reverse-engineering-recurrent-neural-networks-with-jacobian-switching-linear-dynamical-systems Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems |... Nov 1, 2021 - 11/01/21 - Recurrent neural networks (RNNs) are powerful models for processing time-series data, but it remains challenging to understand how... recurrent neural networks reverse engineering https://arxiv.org/abs/1709.08520 [1709.08520] Predictive-State Decoders: Encoding the Future into Recurrent Networks Abstract page for arXiv paper 1709.08520: Predictive-State Decoders: Encoding the Future into Recurrent Networks the future 1709 08520 predictive state https://aclanthology.org/W13-3214/ Recurrent Convolutional Neural Networks for Discourse Compositionality - ACL Anthology Nal Kalchbrenner, Phil Blunsom. Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality. 2013. convolutional neural networks recurrent discourse compositionality acl https://elifesciences.org/articles/73870 Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics... Recurrent neural network models enable prediction and design of health-relevant metabolite dynamics in synthetic human gut communities. recurrent neural networks human gut microbiome design of https://openreview.net/forum?id=NCjlFw1Ab0 Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks | OpenReview Traveling waves are a fundamental phenomenon in the brain, playing a crucial role in short-term information storage. In this study, we leverage the concept of... recurrent neural networks traveling waves working memory https://www.analyticsvidhya.com/blog/2020/10/recurrent-neural-networks-for-sequence-learning/ Recurrent Neural Networks for Sequence Learning Dec 29, 2020 - Recurrent Neural Networks are based on the same principles as FFNN, except the thing that it also takes care of temporal dependencies recurrent neural networks sequence learning https://deepai.org/publication/guided-self-organization-of-input-driven-recurrent-neural-networks Guided Self-Organization of Input-Driven Recurrent Neural Networks | DeepAI Sep 6, 2013 - 09/06/13 - We review attempts that have been made towards understanding the computational properties and mechanisms of input-driven dynamical... recurrent neural networks self organization guided input driven https://aclanthology.org/2020.alta-1.13/ Convolutional and Recurrent Neural Networks for Spoken Emotion Recognition - ACL Anthology Aaron Keesing, Ian Watson, Michael Witbrock. Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association. 2020. recurrent neural networks emotion recognition