nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
1 |
Active learning of causal structures with deep reinforcement learning
|
Amirinezhad, Amir |
|
|
154 |
C |
p. 22-30 |
artikel |
2 |
AdjointBackMap: Reconstructing effective decision hypersurfaces from CNN layers using adjoint operators
|
Wan, Qing |
|
|
154 |
C |
p. 78-98 |
artikel |
3 |
A multi-birth metric learning framework based on binary constraints
|
Ren, QiangQiang |
|
|
154 |
C |
p. 165-178 |
artikel |
4 |
A portable clustering algorithm based on compact neighbors for face tagging
|
Pei, Shenfei |
|
|
154 |
C |
p. 508-520 |
artikel |
5 |
Attention-based random forest and contamination model
|
Utkin, Lev V. |
|
|
154 |
C |
p. 346-359 |
artikel |
6 |
BackEISNN: A deep spiking neural network with adaptive self-feedback and balanced excitatory–inhibitory neurons
|
Zhao, Dongcheng |
|
|
154 |
C |
p. 68-77 |
artikel |
7 |
Brain-inspired meta-reinforcement learning cognitive control in conflictual inhibition decision-making task for artificial agents
|
Robertazzi, Federica |
|
|
154 |
C |
p. 283-302 |
artikel |
8 |
Breaking CAPTCHA with Capsule Networks
|
Mocanu, Ionela Georgiana |
|
|
154 |
C |
p. 246-254 |
artikel |
9 |
Compressing speaker extraction model with ultra-low precision quantization and knowledge distillation
|
Huang, Yating |
|
|
154 |
C |
p. 13-21 |
artikel |
10 |
Context-guided entropy minimization for semi-supervised domain adaptation
|
Ma, Ning |
|
|
154 |
C |
p. 270-282 |
artikel |
11 |
Correntropy based semi-supervised concept factorization with adaptive neighbors for clustering
|
Peng, Siyuan |
|
|
154 |
C |
p. 203-217 |
artikel |
12 |
Deep reinforcement learning guided graph neural networks for brain network analysis
|
Zhao, Xusheng |
|
|
154 |
C |
p. 56-67 |
artikel |
13 |
Distributed optimized dynamic event-triggered control for unknown heterogeneous nonlinear MASs with input-constrained
|
Xia, Lina |
|
|
154 |
C |
p. 1-12 |
artikel |
14 |
Editorial Board
|
|
|
|
154 |
C |
p. ii |
artikel |
15 |
Estimating heading from optic flow: Comparing deep learning network and human performance
|
Maus, Natalie |
|
|
154 |
C |
p. 383-396 |
artikel |
16 |
Event stream learning using spatio-temporal event surface
|
Dong, Junfei |
|
|
154 |
C |
p. 543-559 |
artikel |
17 |
Extended analysis on the global Mittag-Leffler synchronization problem for fractional-order octonion-valued BAM neural networks
|
Xiao, Jianying |
|
|
154 |
C |
p. 491-507 |
artikel |
18 |
Face image-sketch synthesis via generative adversarial fusion
|
Sun, Jianyuan |
|
|
154 |
C |
p. 179-189 |
artikel |
19 |
Federated learning with workload-aware client scheduling in heterogeneous systems
|
Li, Li |
|
|
154 |
C |
p. 560-573 |
artikel |
20 |
Finite-time stability of state-dependent delayed systems and application to coupled neural networks
|
He, Xinyi |
|
|
154 |
C |
p. 303-309 |
artikel |
21 |
Heterogeneous Pseudo-Supervised Learning for Few-shot Person Re-Identification
|
Zhao, Jing |
|
|
154 |
C |
p. 521-537 |
artikel |
22 |
How does the brain represent the semantic content of an image?
|
Xu, Huawei |
|
|
154 |
C |
p. 31-42 |
artikel |
23 |
INN/ENNS/JNNS - Membership Applic. Form
|
|
|
|
154 |
C |
p. II |
artikel |
24 |
INN/ENNS/JNNS - Membership Applic. Form
|
|
|
|
154 |
C |
p. I |
artikel |
25 |
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy
|
Lamb, Alex |
|
|
154 |
C |
p. 218-233 |
artikel |
26 |
Latent neighborhood-based heterogeneous graph representation
|
Xiao, Yang |
|
|
154 |
C |
p. 413-424 |
artikel |
27 |
Mean-square stabilization of impulsive neural networks with mixed delays by non-fragile feedback involving random uncertainties
|
Zhang, Xiaoyu |
|
|
154 |
C |
p. 469-480 |
artikel |
28 |
MRGAT: Multi-Relational Graph Attention Network for knowledge graph completion
|
Dai, Guoquan |
|
|
154 |
C |
p. 234-245 |
artikel |
29 |
Multimodal neural networks better explain multivoxel patterns in the hippocampus
|
Choksi, Bhavin |
|
|
154 |
C |
p. 538-542 |
artikel |
30 |
Multivariate time-series classification with hierarchical variational graph pooling
|
Duan, Ziheng |
|
|
154 |
C |
p. 481-490 |
artikel |
31 |
Neural extraction of multiscale essential structure for network dismantling
|
Liu, Qingxia |
|
|
154 |
C |
p. 99-108 |
artikel |
32 |
Novel optimal trajectory tracking for nonlinear affine systems with an advanced critic learning structure
|
Wang, Ding |
|
|
154 |
C |
p. 131-140 |
artikel |
33 |
PDE-READ: Human-readable partial differential equation discovery using deep learning
|
Stephany, Robert |
|
|
154 |
C |
p. 360-382 |
artikel |
34 |
Periodic event-triggered adaptive tracking control design for nonlinear discrete-time systems via reinforcement learning
|
Tang, Fanghua |
|
|
154 |
C |
p. 43-55 |
artikel |
35 |
Physics guided neural networks for modelling of non-linear dynamics
|
Robinson, Haakon |
|
|
154 |
C |
p. 333-345 |
artikel |
36 |
Predictions on multi-class terminal ballistics datasets using conditional Generative Adversarial Networks
|
Thompson, S. |
|
|
154 |
C |
p. 425-440 |
artikel |
37 |
QMEDNet: A quaternion-based multi-order differential encoder–decoder model for 3D human motion prediction
|
Cao, Wenming |
|
|
154 |
C |
p. 141-151 |
artikel |
38 |
Relational local electroencephalography representations for sleep scoring
|
Brandmayr, Georg |
|
|
154 |
C |
p. 310-322 |
artikel |
39 |
Reservoir computing with 3D nanowire networks
|
Daniels, R.K. |
|
|
154 |
C |
p. 122-130 |
artikel |
40 |
Return of the normal distribution: Flexible deep continual learning with variational auto-encoders
|
Hong, Yongwon |
|
|
154 |
C |
p. 397-412 |
artikel |
41 |
Reward prediction errors, not sensory prediction errors, play a major role in model selection in human reinforcement learning
|
Wu, Yihao |
|
|
154 |
C |
p. 109-121 |
artikel |
42 |
Simultaneous neural network approximation for smooth functions
|
Hon, Sean |
|
|
154 |
C |
p. 152-164 |
artikel |
43 |
SLIDE: A surrogate fairness constraint to ensure fairness consistency
|
Kim, Kunwoong |
|
|
154 |
C |
p. 441-454 |
artikel |
44 |
Sparse signal reconstruction via collaborative neurodynamic optimization
|
Che, Hangjun |
|
|
154 |
C |
p. 255-269 |
artikel |
45 |
Subgraph-aware graph structure revision for spatial–temporal graph modeling
|
Wang, Yuhu |
|
|
154 |
C |
p. 190-202 |
artikel |
46 |
Two-level group convolution
|
Lee, Youngkyu |
|
|
154 |
C |
p. 323-332 |
artikel |
47 |
Using source data to aid and build variational state–space autoencoders with sparse target data for process monitoring
|
Lee, Yi Shan |
|
|
154 |
C |
p. 455-468 |
artikel |