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Decoding high energy physics with AI and machine learning
In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and ...
blockchain6mon
NVIDIA TensorRT-LLM Enhances Encoder-Decoder Models with In-Flight Batching
NVIDIA's TensorRT-LLM now supports encoder-decoder models with in-flight batching ... The Triton TensorRT-LLM backend further enhances performance, making it a suitable choice for production-ready ...
Frontiers6mon
Pneumothorax detection and segmentation from chest X-ray radiographs using a patch-based fully convolutional encoder-decoder network
making it not suitable for situations that require real-time inference under low-resource constraint (e.g., deployment in emergency rooms). For this study, we introduce a patch-based fully ...
Slator8mon
A Primer on Decoder-Only vs Encoder-Decoder Models for AI Translation
unlike encoder-decoder models, which require paired text inputs. The researchers of the latter study, published on September 23, 2024, concluded that “the flexibility and the simpler training setup of ...
GitHub9mon
Running custom encoder-decoder models in onnxruntime-genai
My question is about executing encoder-decoder models with onnx genai runtime. My goal is to convert the DONUT transformer https://arxiv.org/abs/2111.15664, a ...
techxplore1y
Voice at the wheel: Study introduces an encoder-decoder framework for AI systems
The article initially frames the challenge of aligning textual instructions with visual scenes as a mapping task, necessitating the conversion of textual descriptions into vectors that accurately ...
Frontiers2y
3D bi-directional transformer U-Net for medical image segmentation
We designed a novel attention mechanism specifically suitable for network training and ... the technical details in this section. Figure 1. The diagram of the 3DTU framework in an encoder–decoder ...