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https://www.analyticsvidhya.com/events/datahour/datahour-deep-dive-into-graph-neural-nets-for-content-nlp/ DataHour: Deep Dive into Graph Neural Nets for Content NLP Join Anustup in this DataHour to explore Graph Neural Nets for NLP. Learn about graphical architecture models, fundamental GNN definitions, real-world... deep dive neural nets graph content nlp https://slatestarcodex.com/2019/02/18/do-neural-nets-dream-of-electric-hobbits/ Do Neural Nets Dream Of Electric Hobbits? | Slate Star Codex Jul 22, 2020 - Last week OpenAI announced its latest breakthrough. GPT-2 is a language model that can write essays to a prompt, answer questions, and summarize longer works.... dream of electric neural nets hobbits slate star https://www.wolfram.com/language/12/image-computation-for-microscopy/segmentation-using-neural-nets.html.en?footer=lang Segmentation Using Neural Nets: New in Wolfram Language 12 neural nets new in wolfram language segmentation using https://www.amazon.science/blog/accelerating-parallel-training-of-neural-nets Accelerating parallel training of neural nets - Amazon Science Mar 23, 2022 - Earlier this year, we reported a speech recognition system trained on a million hours of data, a feat possible through semi-supervised learning, in which... neural nets accelerating parallel training amazon https://hackaday.com/2018/09/16/turn-yourself-into-a-cyborg-with-neural-nets/ Turn Yourself Into A Cyborg With Neural Nets | Hackaday Sep 16, 2018 - If smartwatches and tiny Bluetooth earbuds are any indications, the future is with wearable electronics. This brings up a problem: developing wearable... neural nets turn cyborg hackaday https://deepai.org/publication/sampling-free-variational-inference-of-bayesian-neural-nets Sampling-Free Variational Inference of Bayesian Neural Nets | DeepAI May 19, 2018 - 05/19/18 - We propose a new Bayesian Neural Net (BNN) formulation that affords variational inference for which the evidence lower bound (ELBO... variational inference neural nets sampling free bayesian https://futurism.com/tag/neural-nets neural nets Archives - Futurism neural nets archives futurism https://openreview.net/forum?id=k9CF4h3muD Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets | OpenReview Linear RNNs optimized with gradient descent have implicit bias leading to solutions with low dimensional state spaces leading to non-trivial extrapolation. neural nets learning low dimensional state https://deepai.org/publication/defgraspnets-grasp-planning-on-3d-fields-with-graph-neural-nets DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets | DeepAI Mar 28, 2023 - 03/28/23 - Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlik... neural nets grasp planning https://simonwillison.net/2009/Jan/25/ocr/ OCR and Neural Nets in JavaScript John dissects the brilliant Greasemonkey script that solves simple captchas using the canvas element and HTML5's getImageData API. neural nets ocr javascript https://openreview.net/forum?id=SyW4Gjg0W Kernel Graph Convolutional Neural Nets | OpenReview Graph kernels have been successfully applied to many graph classification problems. Typically, a kernel is first designed, and then an SVM classifier is... neural nets kernel graph openreview https://arxiv.org/abs/2002.01987 [2002.01987] Function approximation by neural nets in the mean-field regime: Entropic... Abstract page for arXiv paper 2002.01987: Function approximation by neural nets in the mean-field regime: Entropic regularization and controlled McKean-Vlasov... https://art19.com/shows/2355b740-4531-4071-a3ab-5907a95a36d3/episodes/5307dfe8-4481-4714-9c9a-0c9c04a31b62/embed?theme=light-custom&primary_color=%23f48024 From search trees to neural nets, a deep dive into natural language processing a deep dive https://arxiv.org/abs/2109.12337 [2109.12337] Delta Hedging with Transaction Costs: Dynamic Multiscale Strategy using Neural Nets Abstract page for arXiv paper 2109.12337: Delta Hedging with Transaction Costs: Dynamic Multiscale Strategy using Neural Nets https://openreview.net/forum?id=HJeiDpVFPr An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality | OpenReview We propose novel neural network architectures, guaranteed to satisfy the triangle inequality, for purposes of (asymmetric) metric learning and modeling graph... https://arxiv.org/abs/hep-lat/9211031 [hep-lat/9211031] Multigrid meets Neural Nets Abstract page for arXiv paper hep-lat/9211031: Multigrid meets Neural Nets hep lat meets neural nets https://arxiv.org/abs/1905.05897 [1905.05897] Transferable Clean-Label Poisoning Attacks on Deep Neural Nets Abstract page for arXiv paper 1905.05897: Transferable Clean-Label Poisoning Attacks on Deep Neural Nets clean label https://www.cmu.edu/compbio/news/2018/neural-nets-supplant-marker-genes-in-analyzing-single-cell-rna-sequencing.html Neural Nets Supplant Marker Genes in Analyzing Single Cell RNA Sequencing - Joint Carnegie... Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have... single cell rna sequencing https://deepai.org/publication/squeezeseg-convolutional-neural-nets-with-recurrent-crf-for-real-time-road-object-segmentation-from-3d-lidar-point-cloud SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation... Oct 19, 2017 - 10/19/17 - In this paper, we address semantic segmentation of road-objects from 3D LiDAR point clouds. In particular, we wish to detect and c... https://deepai.org/publication/leaky-nets-recovering-embedded-neural-network-models-and-inputs-through-simple-power-and-timing-side-channels-attacks-and-defenses Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing... Mar 26, 2021 - 03/26/21 - With the recent advancements in machine learning theory, many commercial embedded micro-processors use neural network models for a... https://yeswici.com/ PNN - Predictive Neural Nets PNN is a financial artificial intelligence (AI) deep learning machine for portfolio managers to assess and optimize investment assets or create new funds. pnn predictive neural nets https://thoughtbot.com/blog/neural-nets Neural Nets Neural nets are a common buzzword when it comes to the modern world of programming and machine learning. But what is a neural net? Why is it talked about so... neural nets https://www.tomshardware.com/news/nvidia-deep-learning-digits-update,29523.html Nvidia's Deep Learning Updates Build Bigger Neural Nets Faster: Digits 2, cuDNN 3, CUDA 7.5 | Tom's... Jul 7, 2015 - At a machine learning convention in France, Nvidia announced updates to its contributions to Deep Learning. https://arxiv.org/abs/2510.03297 [2510.03297] Convolutional Neural Nets vs Vision Transformers: A SpaceNet Case Study with Balanced... Abstract page for arXiv paper 2510.03297: Convolutional Neural Nets vs Vision Transformers: A SpaceNet Case Study with Balanced vs Imbalanced Regimes https://wandb.ai/wandb_fc/articles/reports/The-effects-of-weight-initialization-on-neural-nets--Vmlldzo1NDc1NjU3 The effects of weight initialization on neural nets the effects weight initialization neural nets https://deepai.org/publication/a-better-way-to-decay-proximal-gradient-training-algorithms-for-neural-nets A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets | DeepAI Oct 6, 2022 - 10/06/22 - Weight decay is one of the most widely used forms of regularization in deep learning, and has been shown to improve generalization... a better way https://openreview.net/forum?id=wHkKTW2wrmm Neural Additive Models: Interpretable Machine Learning with Neural Nets | OpenReview We propose Neural Additive Models that combine some of the expressivity of DNNs with the inherent intelligibility of generalized additive models. machine learning neural additive models nets https://futurism.com/neural-nets-capable-of-text-understanding-from-scratch-without-previously-knowing-words-and-phrases Neural nets capable of text understanding from scratch without previously knowing words and phrases This article demontrates that we can apply deep learning to text understanding from character-level inputs all the way up to abstract text concepts, using...