목록논문 리뷰 (47)

Attention please

[논문 리뷰] Dueling DQN: Dueling Network Architectures for Deep Reinforcement Learning (2016)

이번에 리뷰할 논문은 Dueling Network Architectures for Deep Reinforcement Learning 입니다. https://arxiv.org/abs/1511.06581 Dueling Network Architectures for Deep Reinforcement LearningIn recent years there have been many successes of using deep representations in reinforcement learning. Still, many of these applications use conventional architectures, such as convolutional networks, LSTMs, or auto-encoders..
논문 리뷰/Reinforcement Learning 2025. 4. 22. 04:11
[논문 리뷰] DDQN: Deep Reinforcement Learning with Double Q-learning (2016)

이번에 리뷰할 논문은 Deep Reinforcement Learning with Double Q-learning 입니다.https://arxiv.org/abs/1509.06461 Deep Reinforcement Learning with Double Q-learningThe popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known whether, in practice, such overestimations are common, whether they harm performance, and whether they can generally be pr..
논문 리뷰/Reinforcement Learning 2025. 4. 22. 01:44
[논문 리뷰] DQN: Playing Atari with Deep Reinforcement Learning (2013, 2015)

이번에 리뷰할 논문은 Playing Atari with Deep Reinforcement Learning 입니다.https://arxiv.org/abs/1312.5602 Playing Atari with Deep Reinforcement LearningWe present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a variant of Q-learning, whose input is rawa..
논문 리뷰/Reinforcement Learning 2025. 4. 20. 02:56
[논문 리뷰] Mind with Eyes: from Language Reasoning toMultimodal Reasoning (2025)

이번에 리뷰할 논문은 Mind with Eyes: from Language Reasoning to Multimodal Reasoning 입니다.https://arxiv.org/abs/2503.18071 Mind with Eyes: from Language Reasoning to Multimodal ReasoningLanguage models have recently advanced into the realm of reasoning, yet it is through multimodal reasoning that we can fully unlock the potential to achieve more comprehensive, human-like cognitive capabilities. This surve..
논문 리뷰/Multi-Modal 2025. 4. 10. 18:33
[논문 리뷰] VadCLIP: Adapting Vision-Language Models for Weakly SupervisedVideo Anomaly Detection (2023)

이번에 리뷰할 논문은 VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection 입니다. https://arxiv.org/abs/2308.11681 VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly DetectionThe recent contrastive language-image pre-training (CLIP) model has shown great success in a wide range of image-level tasks, revealing remarkable ability for learning powerfu..
논문 리뷰/Anomaly Detection 2025. 4. 4. 23:43
[논문 리뷰] VQ-GAN: Taming Transformers for High-Resolution Image Synthesis (2021)

이번에 리뷰할 논문은 Taming Transformers for High-Resolution Image Synthesis 입니다.https://arxiv.org/abs/2012.09841 Taming Transformers for High-Resolution Image SynthesisDesigned to learn long-range interactions on sequential data, transformers continue to show state-of-the-art results on a wide variety of tasks. In contrast to CNNs, they contain no inductive bias that prioritizes local interactions. This..
논문 리뷰/Image generation 2025. 3. 28. 15:10
이전 Prev 1 2 3 4 ··· 8 Next 다음