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[DL輪読会]Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
2019/09/13 Deep Learning JP: http://deeplearning.jp/seminar-2/ Read less
[DL輪読会]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
【DL輪読会】Perceiver io a general architecture for structured inputs & outputs
[DL輪読会]Recent Advances in Autoencoder-Based Representation Learning 1. Recent advances in autoencoder-based representation learning include incorporating meta-priors to encourage disentanglement and using rate-distortion and rate-distortion-usefulness tradeoffs to balance compression and reconstruction. 2. Variational autoencoders introduce priors to disentangle latent factors, but recent work agg
2019/02/08 Deep Learning JP: http://deeplearning.jp/seminar-2/
This document discusses self-supervised representation learning (SRL) for reinforcement learning tasks. SRL learns state representations by using prediction tasks as an auxiliary objective. The key ideas are: (1) SRL learns an encoder that maps observations to states using a prediction task like modeling future states or actions; (2) The learned state representations improve generalization and exp
[DL輪読会]SOM-VAE: Interpretable Discrete Representation Learning on Time Series
2019/01/11 Deep Learning JP: http://deeplearning.jp/seminar-2/
2018/09/28 Deep Learning JP: http://deeplearning.jp/seminar-2/
2018/09/10 Deep Learning JP: http://deeplearning.jp/hacks/ Read less
【DL輪読会】"Secrets of RLHF in Large Language Models Part I: PPO"
[DL輪読会]CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
[DL輪読会]Revisiting Deep Learning Models for Tabular Data (NeurIPS 2021) 表形式デー...
2018/06/01 Deep Learning JP: http://deeplearning.jp/seminar-2/
[DL輪読会]Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
[DL輪読会]Deep Recurrent Generative Decoder For Abstractive Text Summarization(EMNLP2017)
[DL輪読会]Xception: Deep Learning with Depthwise Separable Convolutions
Similar to [DL輪読会]Adversarial Feature Matching for Text Generation
【DL輪読会】High-Resolution Image Synthesis with Latent Diffusion ModelsDeep Learning JP
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