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Generative flow networks (GFlowNets) are a family of algorithms that learn a generative policy to sample discrete objects $x$ with non-negative reward $R(x)$.
Steps toward artificial intelligence
Minsky, M · 1961
Earlier work this paper cites.
Prioritized experience replay, 2015
Schaul, T., Quan, J., Antonoglou, I., and Silver, D · 2015
Earlier work this paper cites.
Survey of variation in human transcription factors reveals prevalent dna binding changes
LA, B., A, V., JV, K., JM, R., SS, G., EJ, R., J, W., L, M., KH, K., S, I., T, S., L, S., R, G., N, S., C, C., T, H., S, Y., M, K., MJ, D., M, V., DE, H., and ML., B · 2016
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Sutton, R. S. and Barto, A. G · 2018
Earlier work this paper cites.
Measuring compositionality in representation learning
Andreas, J · 2019
Earlier work this paper cites.
Revisiting fundamentals of experience replay
Fedus, W., Ramachandran, P., Agarwal, R., Bengio, Y., Larochelle, H., Rowland, M., and Dabney, W · 2020
Cited alongside, same era.
Compositionality
Szabó, Z. G · 2020
Cited alongside, same era.
Bayesian structure learning with generative flow networks
Deleu, T., Góis, A., Emezue, C., Rankawat, M., Lacoste-Julien, S., Bauer, S., and Bengio, Y · 2022
Cited alongside, same era.
Biological sequence design with gflownets
Jain, M., Bengio, E., Garcia, A.-H., Rector-Brooks, J., Dossou, B. F. P., Ekbote, C., Fu, J., Zhang, T., Kilgour, M., Zhang, D., Simine, L., Das, P., and Bengio, Y · 2022
Cited alongside, same era.
Learning gflownets from partial episodes for improved convergence and stability, 2022
Madan, K., Rector-Brooks, J., Korablyov, M., Bengio, E., Jain, M., Nica, A., Bosc, T., Bengio, Y., and Malkin, N · 2022
Cited alongside, same era.
Flow network based generative models for non-iterative diverse candidate generation
Bengio, E., Jain, M., Korablyov, M., Precup, D., and Bengio, Y
Cited in the paper.
Bengio, Y., Deleu, T., Hu, E. J., Lahlou, S., Tiwari, M., and Bengio, E
Cited in the paper.
Trajectory balance: Improved credit assignment in gflownets
Malkin, N., Jain, M., Bengio, E., Sun, C., and Bengio, Y · 2022
Later among the works it cites.
Evaluating generalization in GFlownets for molecule design
Nica, A. C., Jain, M., Bengio, E., Liu, C.-H., Korablyov, M., Bronstein, M. M., and Bengio, Y · 2022
Later among the works it cites.
Design-bench: Benchmarks for data-driven offline model-based optimization, 2022
Trabucco, B., Geng, X., Kumar, A., and Levine, S · 2022
Later among the works it cites.
Generative flow networks for discrete probabilistic modeling
Zhang, D., Malkin, N., Liu, Z., Volokhova, A., Courville, A., and Bengio, Y · 2022
Later among the works it cites.
Improving generative flow networks with path regularization
Anonymous · 2023
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