Marktechpost

SEPTEMBER 29, 2024

Google researchers addressed the challenge of variability and subjectivity in clinical experts’ interpretation of visual cardiotocography (CTG), specifically focusing on predicting fetal hypoxia, a dangerous condition of oxygen deprivation during labor, using deep learning techniques. Check out the Paper and Details.

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Deep Learning Convolutional Neural Networks AI Researcher AI Research 64

Marktechpost

DECEMBER 19, 2023

A new AI research introduces TorchExplorer, a novel AI tool designed for researchers working with unconventional neural network architectures, which provides an interactive and insightful exploration of network layers.

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Neural Network Deep Learning AI Tools AI Researcher 108

Marktechpost

NOVEMBER 25, 2023

Addressing this, Jason Eshraghian from UC Santa Cruz developed snnTorch, an open-source Python library implementing spiking neural networks, drawing inspiration from the brain’s remarkable efficiency in processing data. Traditional neural networks lack the elegance of the brain’s processing mechanisms.

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Marktechpost

SEPTEMBER 1, 2023

Artificial intelligence’s allure has long been shrouded in mystique, especially within the enigmatic realm of deep learning. These intricate neural networks, with their complex processes and hidden layers, have captivated researchers and practitioners while obscuring their inner workings.

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Marktechpost

JULY 2, 2023

The exponentially expanding scale of deep learning models is a major force in advancing the state-of-the-art and a source of growing worry over the energy consumption, speed, and, therefore, feasibility of massive-scale deep learning. What happens if you run a Transformer model with an optical neural network?*

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Marktechpost

NOVEMBER 30, 2023

The study finds variability in the status of these core elements by analyzing 32 papers that predict poverty/wealth, using survey data for ground truth, applying it to urban and rural settings, and involving deep neural networks. The goal is to enhance wider dissemination and acceptance within the development community.

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Deep Learning AI Researcher AI Research Neural Network 98

Marktechpost

SEPTEMBER 10, 2023

Researchers think that high-speed testing using Deep Learning models can help us understand these effects better and speed up catalyst development. The way a catalyst’s surface is shaped matters for certain chemical reactions due to various properties of the catalyst, which we study in Surface Chemistry.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Marktechpost

DECEMBER 30, 2023

The remarkable potentials of Artificial Intelligence (AI) and Deep Learning have paved the way for a variety of fields ranging from computer vision and language modeling to healthcare, biology, and whatnot. SciML consists of three primary subfields, which include PDE solvers, PDE discovery, and operator learning.

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Marktechpost

OCTOBER 13, 2023

In the realm of deep learning, the challenge of developing efficient deep neural network (DNN) models that combine high performance with minimal latency across a variety of devices remains. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter. We are also on WhatsApp.

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Marktechpost

JULY 7, 2024

Artificial neural networks (ANNs) traditionally lack the adaptability and plasticity seen in biological neural networks. Overall, LNDPs demonstrated superior adaptation speed and learning efficiency, highlighting their potential for developing adaptable and self-organizing AI systems. Check out the Paper.

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Marktechpost

NOVEMBER 25, 2023

Data augmentation is a critical technique in deep learning that involves creating new training data by modifying existing samples. Creating variations of existing samples prevents overfitting and helps the model learn more robust and adaptable features, which is crucial for accurate predictions in real-world scenarios.

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Neural Network AI Researcher AI Research Deep Learning 120

Marktechpost

OCTOBER 8, 2023

Can we adapt these hierarchy organization and parallel processing techniques in deep learning? Yes, the field of study is called Neural networks. This provides an advantage to NDP as it can operate upon any neural network of arbitrary size or architecture. Join our AI Channel on Whatsapp.

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Neural Network Deep Learning Automation Algorithm 129

Marktechpost

SEPTEMBER 8, 2023

Researchers suggest a new approach to design using heuristic optimization and artificial neural networks to simplify the optimization process drastically. A deep neural network model replaced the 3D electromagnetic simulation of a Si-based MZM. If you like our work, you will love our newsletter.

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Deep Learning Algorithm AI Researcher AI Research 110

Marktechpost

OCTOBER 18, 2023

One of the biggest challenges in Machine Learning has always been to train and use neural networks efficiently. In recent research, a team of researchers has introduced a deep learning compiler specifically made for neural network training.

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Marktechpost

NOVEMBER 8, 2023

Overconfidence is a prevalent issue, particularly in the context of deep neural networks. The team has shared the two primary features of Fortuna that greatly improve deep learning uncertainty quantification. Deep neural networks that are being trained from the start can be trained using these techniques.

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Marktechpost

DECEMBER 15, 2023

Several new innovations have been made possible because of the advancements in the field of Artificial intelligence and Deep Learning. Complex tasks like text or picture synthesis, segmentation, and classification are being successfully handled with the help of neural networks.

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Marktechpost

MARCH 23, 2024

AI researchers are taking the game to a new level with geometric deep learning. DeepMind Researchers introduce TacticAI, an AI assistant designed to optimize one of football’s biggest set-piece weapons: the corner kick. All credit for this research goes to the researchers of this project.

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Marktechpost

JULY 12, 2023

Artificial neural networks have advanced significantly over the past few decades, propelled by the notion that more network complexity results in better performance. Modern technology has amazing processing capacity, enabling neural networks to perform these jobs excellently and efficiently.

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Neural Network Computer Vision AI Researcher AI Research 98

Marktechpost

DECEMBER 28, 2023

Purdue University’s researchers have developed a novel approach, Graph-Based Topological Data Analysis (GTDA), to simplify interpreting complex predictive models like deep neural networks. The method was also applied to study chest X-ray diagnostics and compare deep-learning frameworks, showcasing its versatility.

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Marktechpost

JANUARY 4, 2024

Qu Kun from the University of Science and Technology of the Chinese Academy of Sciences has created a solution called Spatial Architecture Characterization by Deep Learning (SPACEL). The post Meet SPACEL: A New Deep-Learning-based Analysis Toolkit for Spatial Transcriptomics appeared first on MarkTechPost.

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Marktechpost

JULY 24, 2023

With the advent of Machine Learning (ML) and Deep Learning (DL), image and video editing have been progressively studied through several neural network architectures. Check out the paper , code , and project All Credit For This Research Goes To Researchers on This Project.

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Neural Network Artificial Intelligence Artificial Intelligence AI Researcher 96

Marktechpost

SEPTEMBER 3, 2023

Credit assignment in neural networks for correcting global output mistakes has been determined using many synaptic plasticity rules in natural neural networks. Methods of biological neuromodulation have inspired several plasticity algorithms in models of neural networks.

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Marktechpost

SEPTEMBER 8, 2023

It offers a versatile platform not only for neural networks but also for handling a wide range of tasks, including ODEs, SDEs, linear solves, and more. The post Meet Equinox: A JAX library for Neural Networks and sciML appeared first on MarkTechPost. If you like our work, you will love our newsletter.

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Marktechpost

NOVEMBER 16, 2023

Researchers from MIT investigated the scaling behavior of large chemical language models, focusing on both generative pre-trained transformers (GPT) for chemistry (ChemGPT) and graph neural network force fields (GNNs). All credit for this research goes to the researchers of this project. Check out the Paper.

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Deep Learning Neural Network Computer Vision AI 105

Marktechpost

DECEMBER 25, 2023

A considerable amount of research has been done to address this problem, focusing mainly on using artificial neural networks. Therefore, the authors of this research paper from SLAC National Accelerator Laboratory, USA have introduced PtychoPINN. If you like our work, you will love our newsletter.

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Deep Learning Neural Network AI Researcher AI Research 122

Marktechpost

OCTOBER 8, 2023

By utilizing finely developed neural network architectures, we have models that are distinguished by extraordinary accuracy within their respective sectors. Despite their accurate performance, we must still fully understand how these neural networks function. Join our AI Channel on Whatsapp.

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Marktechpost

DECEMBER 11, 2023

A rising number of people are interested in data-driven, deep learning-based weather forecasting methods to overcome the problems with NWP models. Using historical data, like the ERA5 reanalysis dataset, deep neural networks are trained to forecast future weather conditions.

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Marktechpost

JULY 13, 2023

Molecular scientists are hailing the breakthrough accuracy of deep learning approaches like AlphaFold and RoseTTAFold in identifying the most probable structures for proteins from their amino acid sequences. DiG is a deep learning framework for molecular systems that simulates this procedure.

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Deep Learning AI Researcher AI Research Neural Network 98

Marktechpost

NOVEMBER 23, 2023

Researchers have introduced a novel approach using topological data analysis (TDA), to solve the issue. These models, including machine learning, neural networks, and AI models, have become standard tools in various scientific fields but are often difficult to interpret due to their extensive parameterization.

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Marktechpost

SEPTEMBER 8, 2023

So, there has been thorough research conducted by the researchers on QPI and thus researchers from the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA) have introduced a new design for multispectral QPI. If you like our work, you will love our newsletter.

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Neural Network Deep Learning AI Researcher AI Research 111

Marktechpost

NOVEMBER 30, 2023

The constant upliftment of AI and ML approaches has reshaped the possibilities of what machines can accomplish and how humans interact with machines. To overcome the challenge, a team of researchers from Stanford, Kumo AI, Yale, Max Plank, and the University of Illinois at Urbana-Champaign has recently proposed Relational Deep Learning.

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Marktechpost

OCTOBER 1, 2023

Researchers have recently developed Temporal Graph Neural Networks (TGNNs) to take advantage of temporal information in dynamic graphs, building on the success of Graph Neural Networks (GNNs) in learning static graph representation. If you like our work, you will love our newsletter.

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Marktechpost

DECEMBER 23, 2023

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

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Neural Network Machine Learning Natural Language Processing Computer Vision 126

Marktechpost

OCTOBER 22, 2023

In the pursuit of replicating the complex workings of the human sensory systems, researchers in neuroscience and artificial intelligence face a persistent challenge: the disparity in invariances between computational models and human perception. Join our AI Channel on Whatsapp. If you like our work, you will love our newsletter.

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Marktechpost

DECEMBER 30, 2023

A new research paper from CSIRO, Australia, addresses these challenges by introducing a novel solution, ML-SEISMIC, a physics-informed deep neural network designed to align stress orientation data with an elastic model autonomously. In geological investigations, conventional inversion processes have long been the norm.

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Deep Learning ML Neural Network AI Researcher 103

Marktechpost

JULY 2, 2023

Implicit neural representations (INRs) or neural fields are coordinate-based neural networks representing a field, such as a 3D scene, by mapping 3D coordinates to color and density values in 3D space. They perform well in many research areas, including generation, inference, and classification. Want to support us?

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