Harvard University

Latent diffusion models have greatly increased in popularity in recent years. Because their outstanding generating capabilities, these models can produce high-fidelity synthetic datasets that can be added to supervised machine learning pipelines in situations when training...
Rising entry barriers are hindering AI's potential to revolutionize global trade. OpenAI's GPT4 is the most recent big language model to be disclosed. However, the model's architecture, training data, hardware, and hyperparameters are kept secret. Large...

Harvard Researchers Propose a Self-Supervised Deep Learning Algorithm for Fast and Scalable Search of Whole-Slide Images

The necessity for accurate and economical gigapixel image analysis has risen as whole-slide imaging has become more widely used. Deep learning is at the...

Latest Machine Learning Research from Microsoft Exhibit a Neural Network Architecture that, in Polynomial Time, Learns as well as any Efficient Learning Algorithm Describable...

In 1947, the genius mathematician and computer scientist Alan Turing anticipated the current state of machine learning research by stating that a machine should...

A New Artificial Intelligence Diagnostic Tool can Detect Diseases on Chest X-rays Directly from Natural-Language Descriptions Contained in Accompanying Clinical Reports

Most AI models in medical machine learning need labeled or annotated datasets for training since it teaches the models to recognize diseases accurately. Since...

A Recent Research From Harvard and Keio University Researchers Present A New Link Between Dopamine-Based Reward Learning And Machine Learning

A recent research article found a relationship between dopaminergic activity and the TD(temporal difference) learning algorithm, giving basic insights into how the brain links...

Harvard Researchers Introduce A Novel ViT Architecture Called Hierarchical Image Pyramid Transformer (HIPT) That Can Scale Vision Transformers To Gigapixel Images Via Hierarchical Self-Supervised...

Tissue phenotyping is a basic challenge in computational pathology (CPATH), which tries to characterize objective, histopathologic aspects inside gigapixel whole-slide images (WSIs) for cancer...

Researchers From MIT and Harvard Finds When and How a Machine-Learning Model is Capable of Overcoming Dataset Bias

It is no doubt that machine learning has become an inseparable part of our daily lives. Today, ML algorithms recommend movies, goods to buy,...

A Neural Network for Solving and Generating University Level Mathematics Problems Using Program Synthesis

The AI research community widely believed that modern deep learning architectures were not "intelligent" enough to solve advanced mathematical problems. But, previous attempts to...

OpenAI Releases Triton, An Open-Source Python-Like GPU Programming Language For Neural Networks

OpenAI released their newest language, Triton. This open-source programming language that enables researchers to write highly efficient GPU code for AI workloads is Python-compatible...

Researchers from IBM, MIT and Harvard Announced The Release Of DARPA “Common Sense AI” Dataset Along With Two Machine Learning Models At ICML 2021

Building machines that can make decisions based on common sense is no easy feat. A machine must be able to do more than merely...

Cornell and Harvard University Researchers Develops Correlation Convolutional Neural Networks (CCNN): To Determine Which Correlations Are Most Important

A team of researchers from Cornell and Harvard University introduces a novel approach to parse quantum matter and make crucial data distinctions. This proposed...

NVIDIA and Harvard University Researchers Introduce AtacWorks: A Machine Learning Toolkit to Revolutionize Genome Sequencing

Researchers from NVIDIA and Harvard University have introduced a machine learning-driven toolkit called AtacWorks that has the potential to bring about remarkable advancements in genome sequencing. What...

Recent articles

Be the first to know the latest AI research breakthroughs.

X