eLife

Modality-agnostic decoding of vision and language from fMRI

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Microsoft launches 3 new AI models in direct shot at OpenAI and Google

Microsoft launches three in-house AI models for transcription, voice, and image generation, challenging OpenAI and Google ...
EDN

Balun transformers: Linking balanced to unbalanced

Balun transformers remain indispensable in RF and high-frequency design, serving as the quiet interface between balanced transmission lines and unbalanced circuits. By enabling impedance matching, ...
IEEE

Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction

Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
GitHub

Understanding Self-Attention(Encoder's Self-Attention and Decoder's Masked Self-Attention) in Transformers #1

- Driven by the **output**, attending to the **input**. - Each word in the output sequence determines which parts of the input sequence to attend to, forming an **output-oriented attention** mechanism ...
marktechpost

Decoupled Diffusion Transformers: Accelerating High-Fidelity Image Generation via Semantic-Detail Separation and Encoder Sharing

Diffusion Transformers have demonstrated outstanding performance in image generation tasks, surpassing traditional models, including GANs and autoregressive architectures. They operate by gradually ...
GitHub

TSDAE layer initialization of encoder and decoder

I want to train pretrain a sentence transformer using TSDAE. We have previously used all-MiniLM-L6-v2 as a checkpoint where we finetuned with MultipleNegativeRankingLoss with the main downstream task ...