Results 11 to 20 of about 1,645,972 (339)
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2014 In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixed-length vector representation, and the other decodes the ...
Bahdanau, Dzmitry +6 more
core +2 more sources
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-related tasks.
Yue Wang +3 more
semanticscholar +1 more source
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval [PDF]
IEEE International Conference on Computer Vision, 2021 Our objective in this work is video-text retrieval – in particular a joint embedding that enables efficient text-to-video retrieval. The challenges in this area include the design of the visual architecture and the nature of the training data, in that ...
Max Bain +3 more
semanticscholar +1 more source
Long-term Forecasting with TiDE: Time-series Dense Encoder [PDF]
Trans. Mach. Learn. Res., 2023 Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting. Motivated by this, we propose a Multi-layer Perceptron (MLP) based encoder-decoder model, Time-series Dense Encoder (
Abhimanyu Das +5 more
semanticscholar +1 more source
Thermodynamics of Encoding and Encoders
CoRR, 2021 Non-isolated systems have diverse coupling relations with the external environment. These relations generate complex thermodynamics and information transmission between the system and its environment. The framework depicted in the current research attempts to glance at the critical role of the internal orders inside the non-isolated system in shaping ...
Yang Tian, Pei Sun
openaire +2 more sources
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models [PDF]
ACM Transactions on Graphics, 2023 Text-to-image personalization aims to teach a pre-trained diffusion model to reason about novel, user provided concepts, embedding them into new scenes guided by natural language prompts.
Rinon Gal +5 more
semanticscholar +1 more source
Information thermodynamics of encoding and encoders
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 Non-isolated systems have diverse coupling relations with the external environment. These relations generate complex thermodynamics and information transmission between the system and its environment. The framework depicted in the current research attempts to glance at the critical role of the internal orders inside the non-isolated system in shaping ...
Yang Tian, Pei Sun
openaire +2 more sources
Designing an encoder for StyleGAN image manipulation [PDF]
ACM Transactions on Graphics, 2021 Recently, there has been a surge of diverse methods for performing image editing by employing pre-trained unconditional generators. Applying these methods on real images, however, remains a challenge, as it necessarily requires the inversion of the ...
Omer Tov +4 more
semanticscholar +1 more source
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by ...
Vijay Badrinarayanan +2 more
semanticscholar +1 more source
Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers [PDF]
IEEE International Conference on Computer Vision, 2021 Transformers are increasingly dominating multi-modal reasoning tasks, such as visual question answering, achieving state-of-the-art results thanks to their ability to contextualize information using the self-attention and co-attention mechanisms.
Hila Chefer, Shir Gur, Lior Wolf
semanticscholar +1 more source