Microsoft Researchers Unlock New Avenues In Image-Generation Research With Manifold Matching Via Metric Learning

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By developing fresh images, generative image models provide a distinct value. These photos could be clear super-resolution copies of current images or even manufactured...

Google AI Improves The Performance Of Smart Text Selection Models By Using Federated Learning

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Smart Text Selection is one of Android's most popular features, assisting users in selecting, copying, and using text by anticipating the desired word or...

NVIDIA Open-Source ‘FLARE’ (Federated Learning Application Runtime Environment), Providing A Common Computing Foundation For...

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Standard machine learning methods involve storing training data on a single machine or in a data center. Federated learning is a privacy-preserving technique that...

Ericsson And Uppsala University Team Up To Research Air Quality Prediction Using Machine Learning...

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Statistical methods have recently been applied in various sectors, spanning from health care to customer relationship management, to analyze and forecast the behavior of...

Google Research Open-Sources ‘SAVi’: An Object-Centric Architecture That Extends The Slot Attention Mechanism...

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Multiple distinct things act as compositional building blocks that can be processed independently and recombined in humans' understanding of the world. The foundation for...

Apple Researchers Propose A Method For Reconstructing Training Data From Diverse Machine Learning Models...

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Model inversion (MI), where an adversary abuses access to a trained Machine Learning (ML) model in order to infer sensitive information about the model's...

Scientists Use A New Deep Learning Method To Add 301 Planets to Kepler’s Total...

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Deep neural networks are machine learning systems that automatically learn a task if provided with necessary data.  An artificial neural network (ANN) having numerous...

MetaICL: A New Few-Shot Learning Method Where A Language Model Is Meta-Trained To Learn...

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Large language models (LMs) are capable of in-context learning, which involves conditioning on a few training examples and predicting which tokens will best complete...

NVIDIA Introduces GauGAN2: An AI Model That Converts Text Into Images

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Nvidia has introduced a new AI model called GauGAN2, the successor to its original and most famous “GauGAN” model. This time around they're letting...

Microsoft Research Introduces ‘Tutel’: A High-Performance MoE Library To Facilitate The Development Of Large-Scale...

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'The Mixture of Experts (MoE) architecture is a deep learning model architecture in which the computational cost is proportional to the number of parameters,...

Google Highlights How Statistical Uncertainty Of Outcomes Must Be Considered To Evaluate Deep RL...

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Reinforcement Learning (RL) is a machine learning technique that allows an agent to learn by trial and error in an interactive environment from its...

TensorFlow Introduces TensorFlow Graph Neural Networks (TF-GNNs)

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In the actual world and also in engineered systems, graphs are everywhere. A graph is a representation of a collection of entities such as...

Meta/Facebook AI Releases XLS-R: A Self-Supervised Multilingual Model Trained On 128 Languages For A...

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Talking to one another is a natural way for people to engage. With advancing speech technology, people are now interacting with devices in day...

A New Research On Unsupervised Deep Learning Shows That The Brain Disentangles Faces Into...

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The ventral visual stream is widely known for supporting the perception of faces and objects. Extracellular single neuron recordings define canonical coding principles at...

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