• Introduction
  • Finished List
    • Bayesian Machine Learning
    • Deep Learning
    • Finance/Quant Finance
    • General CS
    • General Data Science
    • Machine Learning
    • Numerical and Optimization
    • Traditional Statistics
    • Books
    • Broker Reports
    • Quant Finance Notes
    • Machine Learning Notes
    • Factor Calendar
    • Temp files
    • O3-mini files
  • Reading List
    • Bayesian Machine Learning
    • Deep Learning
    • Machine Learning
    • Numerical and Optimization
    • Traditional Statistics
    • Books
  • Notes
    • Neural ODE
    • Relational Dependency Networks
    • LDA
    • KSD for Goodness-of-fit Tests
    • LTK Goodness-of-Fit Test
    • Sample Complexity Bounds for Gaussian Mixtures
    • A Complete Recipe for SGMCMC
    • Sharpe Minima Can Generalize
    • Large Batch Training and Sharpe Minima
    • Riemann Manifold Langevin and HMC
    • Path-SGD: Path-normalized Optimization in Deep Neural Networks
    • Empirical Analysis of DNN Loss Surfaces
    • Good Semi-supervised Learning that Requires a Bad GAN
    • Faster Rates for Frank-Wolfe over Strongly-Convex Sets
    • The Element of Financial Econometrics
    • Double machine learning for treatment effect
    • Part 1: Reinforcement Learning: An Introduction
    • Part 2: Reinforcement Learning: An Introduction (2)
    • Trust Region Policy Optimization
    • Prioritized Experience Replay
    • A Galtonian Perspective on Shrinkage Estimators
    • Regression Shrinkage and Selection via the Lasso
    • Nonparametric Instrumental Regression
    • Decentralized mining in centralized pools
    • Majority is not enough: Bitcoin mining is vulnerable
    • Lazy Prices
    • Confidence Intervals for Policy Evaluation in Adaptive Experiments
    • Statistical Inference with M-Estimators on Adaptively Collected Data
    • Realized Variance and Market Microstructure Noise
    • Blockchain without waste: Proof-of-stake
    • Crowdsourced employer reviews and stock returns
    • A Survey of Attacks on Ethereum Smart Contracts
    • Technological Links and Predictable Returns
    • Extrapolative beliefs in the cross-section: What can we learn from the crowds?
    • Geographic Lead-Lag Effects
    • Shared Analyst Coverage: Unifying Momentum Spillover Effects
    • Q-Factor Model
    • Short- and Long-Horizon Behavioral Factors
    • Stambaugh-Yuan Four Factors
    • Chinese NLP
    • Chinese Stock Market Shell Value
    • Size and Value
    • Tracking Retail Investor Activity
    • Graph Convolution and Graph Attention
    • P-hacking
    • General Structures and Techniques in Deep Learning
    • Temporal Convolutional Network
    • Which Beta?
    • Out of Sample Predictability
    • Multi-factor in Cryptocurrency
    • Quant Machine Learning
    • Behavioral Finance
    • Nonlinear Dimension Reduction
    • Momentum
    • Lottery-like Stocks
    • TabNet
    • Kaggle Finance Competition Solution Summary
    • Feature Interaction
    • ESG
    • Idiosyncratic Volatility
    • Volume
    • Overnight Return Reserval
    • Neural Architecture Search
    • Meta Learning
    • Nominal Price Ilusion
    • Co-trade Network
    • Order Imbalance with Trade Flow Decomposition
    • Time Seris Machine Learning
    • PEAD
    • Risk Parity
    • NLP in Finance
    • Self-supervised Learning for Tabular Data
    • Regime Modeling
    • Financial Statement Related
    • Deep Learning in Finance
  • Published with GitBook

TabNet

  • TabNet

TabNet

  • Arik, Sercan Ö., and Tomas Pfister. "Tabnet: Attentive interpretable tabular learning." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 8, pp. 6679-6687. 2021.
  • 数据挖掘竞赛利器——TabNet模型浅析
  • TabNet-为表格数据而生

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