This is the official repository of paper Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching. We propose Distilled Decoding (DD) to distill a pre-trained image ...

Brain–computer interfaces are beginning to truly "understand" Chinese. The INSIDE Institute for NeuroAI, in collaboration with Huashan Hospital affiliated with Fudan University, the National Center ...

Our ECoG to Speech decoding framework is initially described in A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis. We present a novel deep learning-based neural speech ...

Earlier this year, two hackers broke into a computer and soon realized the significance of what this machine was. As it turned out, they had landed on the computer of a hacker who allegedly works for ...

Scientists have pinpointed brain activity related to inner speech—the silent monolog in people's heads—and successfully decoded it on command with up to 74% accuracy. "This is the first time we've ...

As Gen Z slang cycles in and out faster than any parent (and even a 20-year-old, hi!), can keep up with, it’s easy for terms to get lost in translation. And we get it — we’re not the intended audience ...

University of California, Davis researchers have developed a brain-computer interface (BCI) that enables computer cursor control and clicking, using neural signals from the speech motor cortex. One ...

Investors with a lot of money to spend have taken a bearish stance on Super Micro Computer (NASDAQ:SMCI). And retail traders should know. We noticed this today when the trades showed up on publicly ...

Researchers have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). This research presents an innovative approach for implementing energy-efficient adaptive ...

Whales with a lot of money to spend have taken a noticeably bullish stance on Super Micro Computer. Looking at options history for Super Micro Computer (NASDAQ:SMCI) we detected 11 trades. If we ...

Abstract: This paper presents the use of a hierarchical hidden Markov model (H2M2) for decoding brain signals from a tetraplegic patient. The H2M2 is a dynamic classifier used in this study to decode ...