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+# Fully Neural Network based Model for General Temporal Point Process(Neurips 2019,Takahiro Omi)
+
+This code is pytorch version of implementation for Neural Temporal Point Process.
+
+Temporal Point Process is mathematical model for capturing patterns of discrete event occurrences.
+  However, the traditional point process have limited expressivity by assumption.
+  For example, Poisson process assumes the independence of all events though it changes by time.
+  Other point process like Hawkes process does not assume the independence but the intensity function
+  of Hawkes process should be positive and have exponential decaying kernel. For these reason, the author
+  suggest the generalized version of point process by introducing neural network.  
+
+
+Reference
+
+github : https://github.com/omitakahiro/NeuralNetworkPointProcess 
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+
+