| 1990 | - | Finding structure in time - Elman | :: | 49 |
| 1957 | - | Syntactic structures - Chomsky | :: | 40 |
| 1999 | - | Toward a connectionist model of recursion in human linguistic performance - Christiansen,Chater | :: | 14 |
| 1989 | - | A learning algorithm for continually running fully recurrent neural networks - Williams,Zipser | :: | 4 |
| 1989 | - | Graded state machines: the representation of temporal contingencies in Simple Recurrent Networks - Servan-Schreiber,Cleeremans,McClelland | :: | 4 |
| 2000 | - | Natural language grammatical inference with recurrent neural networks - Lawrence,Giles,Fong | :: | 3 |
| 1994 | - | The origin of clusters in recurrent neural network state space - Kolen | :: | 2 |
| 1994 | - | Recurrent networks: state machines or iterated function systems - Kolen | :: | 2 |
| 1990 | - | Backpropagation through time; what it does and how to do it - Werbos | :: | 2 |
| 1998 | - | Enhanced multistream Kalman filter training for recurrent networks - Feldkamp,Prokhorov,Eagen,Yuan | :: | 1 |
| 1995 | - | Gradient-based learning algorithms for recurrent networks and their computational complexity - Williams,Zipser | :: | 1 |
| 1997 | - | Aspects of anaphora resolution in artificial neural networks: Implications for nativism - Parfitt | :: | 1 |
| 2000 | - | Dual EKF methods - Wan,Nelson | :: | 1 |
| 2003 | - | Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets - erez-Ortiz,Schmidhuber | :: | 1 |
| 1995 | - | An introduction to the Kalman filter - Welch,Bishop | :: | 1 |
| 1996 | - | The power of amnesia: learning probabilistic automata with variable memory length - Ron,Singer,Tishby | :: | 1 |
| 2002 | - | On the emergence of rules in neural networks - Hanson,Negishi | :: | 1 |