Papers Review

1.[NLP] Large Language Models are Zero-Shot Reasoners

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2.[추천시스템] Collaborative Filtering for Implicit Feedback Datasets (ALS)

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4.[딥러닝] Averaging Weights Leads to Wider Optima and Better Generalization (SWA)

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6.[딥러닝] Decoupled Neural Interfaces using Synthetic Gradients (DNI)

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7.[딥러닝] The Forward-Forward Algorithm: Some Preliminary Investigations (FF)

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8.[시계열] Time-Series Anomaly Detection Service at Microsoft (SRCNN)

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9.[딥러닝] Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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10.[추천시스템] Variational Autoencoders for Collaborative Filtering (MultVAE)

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11.[Vision] MLP-Mixer: An all-MLP Architecture for Vision

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12.[Vision] Generative Adversarial Nets (GAN)

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13.[NLP] Attention Is All You Need (Transformer)

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14.[딥러닝] Layer Collaboration in the Forward-Forward Algorithm

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15.[딥러닝] Bootstrap Your Own Latent : A New Approach to Self-Supervised Learning (BYOL)

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16.[신경과학] Serotonin neurons modulate learning rate through uncertainty

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17.[딥러닝] VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

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18.[딥러닝] β-VAE : Learning basic visual concepts with a constrained variational framework

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19.[추천시스템] Representation Learning with Large Language Models for Recommendation

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