Catch up with the fast moving field of data science. Even for us it has been difficult to stay up to date with the latest news and developments in the industry. We are putting together some of the top sources such as MIT, NVIDIA, ARXIV and others. These articles are aggregated from well trusted sources in the community. We will continue to add more sources and refine the type of articles showcased here over time.
Data Science
The recent developments in the field of data science and AI. Sources: Explosion.ai, Rasa, fast.ai, MIT, Berkley, Uber, IBM and Google AI Blog and other trusted sources.
- Speeding up drug discovery with diffusion generative modelsby Alex Ouyang | Abdul Latif Jameel Clinic for Machine Learning in Health on March 31, 2023 at 1:55 pm
MIT researchers built DiffDock, a model that may one day be able to find new drugs faster than traditional methods and […]
- A method for designing neural networks optimally suited for certain tasksby Adam Zewe | MIT News Office on March 30, 2023 at 7:30 pm
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam […]
- Data-centric ML benchmarking: Announcing DataPerf’s 2023 challengesby Google AI on March 30, 2023 at 5:05 pm
Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google […]
- Bacterial injection system delivers proteins in mice and human cellsby Allessandra DiCorato | Broad Institute | McGovern Institute for Brain Research on March 29, 2023 at 3:00 pm
With further development, the programmable system could be used in a range of applications including gene and cancer […]
- Leveraging transfer learning for large scale differentially private image classificationby Google AI on March 28, 2023 at 6:26 pm
Posted by Harsh Mehta, Software Engineer, and Walid Krichene, Research Scientist, Google Research Large deep […]
News
- Speeding up drug discovery with diffusion generative models – MIT Newson March 31, 2023 at 1:55 pm
Speeding up drug discovery with diffusion generative models MIT News
- Machine learning algorithm sets SHIB price for April 30, 2023 – Finbold – Finance in Boldon March 31, 2023 at 1:52 pm
Machine learning algorithm sets SHIB price for April 30, 2023 Finbold – Finance in Bold
- US national lab uses machine learning to detect rogue nuclear threats – TechSpoton March 31, 2023 at 1:08 pm
US national lab uses machine learning to detect rogue nuclear threats TechSpot
- Study suggests available deep learning software does not enhance assessment of bi-parametric prostate MRI – Urology Timeson March 31, 2023 at 12:54 pm
Study suggests available deep learning software does not enhance assessment of bi-parametric prostate MRI Urology Times
- WiMi Develops Deep Learning-Based 3D Target Recognition Algorithm System – Marketscreener.comon March 31, 2023 at 12:01 pm
WiMi Develops Deep Learning-Based 3D Target Recognition Algorithm System Marketscreener.com
White Papers
Latest research and developments in the field of machine learning and deep learning. Sources: ARXIV, Papers with Code and others
- Are Neural Architecture Search Benchmarks Well Designed? A Deeper Look Into Operation Importance. (arXiv:2303.16938v1 [cs.LG])
Neural Architecture Search (NAS) benchmarks significantly improved the capability of developing and comparing NAS […]
- SoftCLIP: Softer Cross-modal Alignment Makes CLIP Stronger. (arXiv:2303.17561v1 [cs.CV])
During the preceding biennium, vision-language pre-training has achieved noteworthy success on several downstream […]
- Quantum Circuit Fidelity Improvement with Long Short-Term Memory Networks. (arXiv:2303.17523v1 [quant-ph])
Quantum computing has entered the Noisy Intermediate-Scale Quantum (NISQ) era. Currently, the quantum processors we […]
- ProContEXT: Exploring Progressive Context Transformer for Tracking. (arXiv:2210.15511v4 [cs.CV] UPDATED)
Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template. This causes tracking […]
- Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features. (arXiv:2210.06756v2 [cs.CV] UPDATED)
Decoding human visual neural representations is a challenging task with great scientific significance in revealing […]