Search Results - computational+efficiency

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Subgraph Matching for High-Throughput DNA-Aptamer Secondary Structure Classification and Machine Learning Interpretability (Case No. 2025-104)
Intro Sentence: UCLA researchers in the Department of Mathematics have developed machine learning methods to rapidly identify novel aptamer sequences for target binding to accelerate highly-accurate diagnostic and therapeutic development. Background: Aptamers are single-stranded nucleotide polymers that bind with high affinity to targets such as...
Published: 7/22/2025   |   Inventor(s): Andrea Bertozzi, Anne Andrews, Matthew Tyler, Paolo Climaco, Noelle Mitchell
Keywords(s): Advanced Computing / AI, advanced computing methods, Aptamers, Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence/machine learning models, bioinformatics pipeline, cancer target, clustering, computational efficiency, computational efficiency and analysis, design software, DNA clustering, DNA oligomer, DNA Sequencing, Drug, Drug Delivery, Drug Development, Drug Discovery, drug screening, high throughput, high throughput assays, high throughput testing, high-throughput analysis, High-Throughput Screening, interpretability, pipeline, large-scale parallelization, Machine Learning, machine learning modeling, motif structures, open source, open source code, OpenAI, Pharmaceutical Drug, protein classification, secondary structure, SELEX, sequences of interest, single strand DNA sequences, Software, Software & Algorithms, Software Development Tools, Software-enabled learning, subgraph matching, target binding, target detection, Targeted Therapy, Targets And Assays, tissue targeting accuracy
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Data Analytics, Life Science Research Tools, Life Science Research Tools > Research Methods, Life Science Research Tools > Screening Libraries, Platforms, Platforms > Drug Delivery, Diagnostic Markers > Targets And Assays, Diagnostic Markers, Software & Algorithms > Bioinformatics
Event-Driven Integrate and Fire (EIF) Neuron Circuit for Neuromorphic Computing System (Case No. 2024-275)
Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed an energy efficient neuromorphic computing architecture. Background: Widespread growth in demand for artificial intelligence systems has highlighted limitations in current central processing unit (CPU) designs, particularly in terms of energy efficiency...
Published: 3/4/2025   |   Inventor(s): Mau-Chung Chang, Chao Jen Tien, Yong Hei
Keywords(s): Advanced Computing / AI, advanced computing methods, AI hardware, analog computing, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial intelligence-generated content, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial presenting cells, artificial-intelligent materials, Cloud Computing, computational efficiency, computational imaging, compute-in-memory, Computer Aided Learning, Computer Architecture, Computer Monitor, Computer Vision, CPU design, deep neural networks (DNN), Energy Density, Energy Efficiency, event-driven processing, generative artificial intelligence, latency encoding, low latency computing, low-power architecture, matrix multiplication, Medical artificial intelligence (AI), Neuromorphic computing, offline learning, online learning, spike neural networks (SNN), Supercomputer
Category(s): Electrical, Electrical > Signal Processing, Electrical > Electronics & Semiconductors, Electrical > Computing Hardware, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning
Efficient Stochastic Compute-In-Memory Circuit for Multi-Level OR Accumulation (Case No. 2024-122)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel computational hardware that combines stochastic computing with compute-in-memory techniques that improves speed and computational efficiency. Background: In recent years, the need for advanced computational technologies has surged, driven by...
Published: 2/14/2025   |   Inventor(s): Sudhakar Pamarti, Jiyue Yang, Soumitra Pal, Puneet Gupta, Tianmu Li, Wojciech Romaszkan
Keywords(s): computational efficiency, Computer Architecture, Integrated Circuit, Logic Gate, neural network, Stochastic Computing (SC)
Category(s): Electrical > Computing Hardware, Electrical > Electronics & Semiconductors > Circuits
Synaptic Circuits Made From Transistors and Memory Capacitors (UCLA Case No. 2023-092)
Summary: UCLA researchers from the Department of Mechanical and Aerospace Engineering have developed a novel circuit architecture that emulates neural synapses for concurrent parallel computing. Background: Almost all modern computer chips consist of computing and learning processes that are implemented sequentially. To improve computing power,...
Published: 2/14/2025   |   Inventor(s): Yong Chen, Zixuan Rong
Keywords(s): Application-Specific Integrated Circuit, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence augmentation, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial-intelligent materials, autonomous control, computational efficiency, edge computing, Electronics & Semiconductors, Energy Efficiency, energy management, Integrated Circuit, Medical artificial intelligence (AI), Neuromorphic circuits, parallel processing, parallel signal processing, processor design, Semiconductor, semiconductor chip foundries, Semiconductor Device, Semiconductors, synaptic resistor (synstor)
Category(s): Electrical, Electrical > Electronics & Semiconductors, Electrical > Signal Processing, Materials, Materials > Semiconducting Materials, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning