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Report NEP-CMP-2021-03-01
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Jean-Franc{c}ois Chassagneux & Junchao Chen & Noufel Frikha & Chao Zhou, 2021, "A learning scheme by sparse grids and Picard approximations for semilinear parabolic PDEs," Papers, arXiv.org, number 2102.12051, Feb.
- Alexandre Carbonneau & Fr'ed'eric Godin, 2021, "Deep Equal Risk Pricing of Financial Derivatives with Multiple Hedging Instruments," Papers, arXiv.org, number 2102.12694, Feb.
- Emiliano Álvarez & Marcelo Álvez & Juan Gabriel Brida, 2020, "Impuesto progresivo al ingreso y crecimiento. Abordaje desde la complejidad," Documentos de trabajo, Banco Central del Uruguay, number 2020008.
- Tengyuan Liang & Pragya Sur, 2020, "A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-152.
- Ivan Jericevich & Dharmesh Sing & Tim Gebbie, 2021, "CoinTossX: An open-source low-latency high-throughput matching engine," Papers, arXiv.org, number 2102.10925, Feb.
- Luisa Roa & Andr'es Rodr'iguez-Rey & Alejandro Correa-Bahnsen & Carlos Valencia, 2021, "Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data," Papers, arXiv.org, number 2102.09974, Feb.
- Tetsuya Kaji & Elena Manresa & Guillaume Pouliot, 2020, "An Adversarial Approach to Structural Estimation," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-144.
- Brotherhood, L. & Cavalcanti, T. & Da Mata, D. & Santos, C., 2020, "Slums and Pandemics," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2076, Aug.
- Bernardo Alves Furtado, 2021, "PolicySpace2: modeling markets and endogenous public policies," Papers, arXiv.org, number 2102.11929, Feb, revised Oct 2021.
- Tengyuan Liang & Hai Tran-Bach, 2020, "Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-151.
- Elena Miola & Marco Manzo, 2021, "A Tax-Benefit Microsimulation Model for Personal Income Taxation in Italy," Working Papers, Ministry of Economy and Finance, Department of Finance, number wp2021-10, Jan.
- Xiuqin Xu & Ying Chen, 2021, "Deep Stochastic Volatility Model," Papers, arXiv.org, number 2102.12658, Feb.
- Tengyuan Liang, 2020, "How Well Generative Adversarial Networks Learn Distributions," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-154.
- Zhen Zeng & Tucker Balch & Manuela Veloso, 2021, "Deep Video Prediction for Time Series Forecasting," Papers, arXiv.org, number 2102.12061, Feb, revised Nov 2021.
- Saïd Assar & Christine Balagué & Loréa Baïada-Hirèche, 2020, "EISAI: Ethical Information System based on Artificial Intelligence," Post-Print, HAL, number hal-03123998, Dec.