--- title: "Neural Networks 2023 — all accepted papers, page 7" description: "All 643 papers of Neural Networks 2023 · page 7 of 7, the most cited first; those with our summary link to it." canonical: "https://research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/7/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/7/) [home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Neural Networks](https://md.research.elamur.ai/free/en/venues/neural-networks/) / [2023](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/) / [papers](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/) / page 7 # Neural Networks 2023: all accepted papers 643 papers · page 7 of 7 · the most cited first · [← Neural Networks 2023](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/) [← prev](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/6/) [1](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/) … [6](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/6/) **7** 601. **[Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors ↗](https://doi.org/10.1016/j.neunet.2023.05.013)**Norikazu Takahashi, T. Yamakawa, Yasuhiro Minetoma et al.*2 citations* 602. **[Enhanced covertness class discriminative universal adversarial perturbations ↗](https://doi.org/10.1016/j.neunet.2023.06.006)**Haoran Gao, Hua Zhang, Xin Zhang et al.*2 citations* 603. **[Incorrect Application of Yilmaz–Poli (2022) Initialisation Method in dePater–Mitici 2023 paper entitled “A mathematical framework for improved weight initialization of neural networks using Lagrange multipliers” ↗](https://doi.org/10.1016/j.neunet.2023.09.017)**Riccardo Poli, Ahmet Yılmaz*2 citations* 604. **[RepCo: Replenish sample views with better consistency for contrastive learning ↗](https://doi.org/10.1016/j.neunet.2023.09.004)**Xinyu Lei, Longjun Liu, Yi Zhang et al.*2 citations* 605. **[A surge of submissions ↗](https://doi.org/10.1016/j.neunet.2023.11.054)**Taro Toyoizumi, Deliang Wang*1 citation* 606. **[Boosting fine-tuning via Conditional Online Knowledge Transfer ↗](https://doi.org/10.1016/j.neunet.2023.10.035)**Zhiqiang Liu, Yuhong Li, Yuhong Li et al.*1 citation* 607. **[Deep learning in random neural fields: Numerical experiments via neural tangent kernel ↗](https://doi.org/10.1016/j.neunet.2022.12.020)**Kaito Watanabe, Kotaro Sakamoto, Ryo Karakida et al.*1 citation* 608. **[Effects of parity, frustration, and stochastic fluctuations on integrated conceptual information for networks with two small-sized loops ↗](https://doi.org/10.1016/j.neunet.2023.02.034)**Tadaaki Hosaka*1 citation* 609. **[Genetic data visualization using literature text-based neural networks: Examples associated with myocardial infarction ↗](https://doi.org/10.1016/j.neunet.2023.05.015)**Ji-Hye Moon, Hugo Fernando Posada-Quintero, Ki H. Chon*1 citation* 610. **[Learning to Generate Tips from Song Reviews ↗](https://doi.org/10.1016/j.neunet.2023.01.049)**Jingya Zang, Cuiyun Gao, Yupan Chen et al.*1 citation* 611. **[Multiple-instance ensemble for construction of deep heterogeneous committees for high-dimensional low-sample-size data ↗](https://doi.org/10.1016/j.neunet.2023.08.028)**Qinghua Zhou, Shuihua Wang‎, Hengde Zhu et al.*1 citation* 612. **[PIPER: A logic-driven deep contrastive optimization pipeline for event temporal reasoning ↗](https://doi.org/10.1016/j.neunet.2023.04.020)**Beibei Zhang, Lishuang Li*1 citation* 613. **[Reinforced mixture learning ↗](https://doi.org/10.1016/j.neunet.2023.05.018)**Yuan Le, Fan Zhou, Yang Bai*1 citation* 614. **[Value iteration for streaming data on a continuous space with gradient method in an RKHS ↗](https://doi.org/10.1016/j.neunet.2023.07.036)**Jiamin Liu, Wangli Xu, Yue Wang et al.*1 citation* 615. **[A dynamical model of visual motion processing for arbitrary stimuli including type II plaids ↗](https://doi.org/10.1016/j.neunet.2023.02.039)**Yusuke Korai, Kenichiro Miura 616. **[A scalable second order optimizer with an adaptive trust region for neural networks ↗](https://doi.org/10.1016/j.neunet.2023.09.010)**Donghee Yang, Junhyun Cho, Sungchul Lee 617. **[AdjointBackMapV2: Precise reconstruction of arbitrary CNN unit’s activation via adjoint operators ↗](https://doi.org/10.1016/j.neunet.2023.11.009)**Qing Wan, Siu Wun Cheung, Yoonsuck Choe 618. **[Announcement of the Neural Networks Best Paper Award ↗](https://doi.org/10.1016/s0893-6080(23)00714-1)** 619. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00152-1)** 620. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00241-1)** 621. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00317-9)** 622. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00476-8)** 623. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00545-2)** 624. **[CURRENT EVENTS ↗](https://doi.org/10.1016/s0893-6080(23)00593-2)** 625. **[Current Events ↗](https://doi.org/10.1016/s0893-6080(22)00519-6)** 626. **[Current Events ↗](https://doi.org/10.1016/s0893-6080(23)00105-3)** 627. **[Current Events ↗](https://doi.org/10.1016/s0893-6080(23)00198-3)** 628. **[Current Events ↗](https://doi.org/10.1016/s0893-6080(23)00410-0)** 629. **[Current Events ↗](https://doi.org/10.1016/s0893-6080(23)00715-3)** 630. **[FCPN: Pruning redundant part-whole relations for more streamlined pattern parsing ↗](https://doi.org/10.1016/j.neunet.2023.10.021)**Zhongqi Lin, Zengwei Zheng 631. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(22)00520-2)** 632. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00106-5)** 633. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00153-3)** 634. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00199-5)** 635. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00242-3)** 636. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00411-2)** 637. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00478-1)** 638. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00546-4)** 639. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00594-4)** 640. **[INN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00716-5)** 641. **[LoyalDE: Improving the performance of Graph Neural Networks with loyal node discovery and emphasis ↗](https://doi.org/10.1016/j.neunet.2023.05.023)**Haotong Wei, Yinlin Zhu, Xunkai Li et al. 642. **[NN/ENNS/JNNS - Membership Applic. Form ↗](https://doi.org/10.1016/s0893-6080(23)00318-0)** 643. **[Neural Networks Referees in 2023 ↗](https://doi.org/10.1016/s0893-6080(23)00713-x)** [← prev](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/6/) [1](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/) … [6](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/papers/page/6/) **7** - [← back to](https://md.research.elamur.ai/free/en/venues/neural-networks/2023/) — Neural Networks 2023