Calculate intensity mu_{c_i} for c_i in "events"; :param sample_dict is a dictionary contains a batch of samples

Calculate intensity mu_{c_i} for c_i in "events"; :param sample_dict is a dictionary contains a batch of samples

Calculate the intensity of event mu_{c_i} for c_i in "events"; :param sample_dict is a dictionary contains a batch of sa

Calculate the intensity of events phi_{c_i,c_j}(t_i - t_j) for c_i in "events"; :param sample_dict is a dictionary conta

Calculate the intensity of event phi_{c_i,c_j}(t_i - t_j) for c_i in "events"; :param sample_dict is a dictionary contai

Calculate the intensity of events phi_{c_i,c_j}(t_i - t_j) for c_i in "events"; :param sample_dict is a dictionary conta

Calculate the intensity of event phi_{c_i,c_j}(t_i - t_j) for c_i in "events"; :param sample_dict is a dictionary contai

Load pre-trained model :param full_path: the path of directory :param mode: 'parameter' for saving only parameters of the

load sequences' features from a csv file :param file_name: the path and the name of the csv file :param seq_domain: the name of the ke

Plot the stem plot of exogenous intensity functions for all event types Args: :param mu_all: a (num_type, 1) FloatTensor c

Plot endogenous impact function for all event types Args: :param infect: a (num_type, num_type+1, M) FloatTensor containin

Predict the expected number of events in the proposed target time window :param history: historical observations histo

Predict the expected number of events in the proposed target time window :param history: historical observations histo

Print basic information of the model.

Print basic information of the exogenous intensity function.

Print basic information of the exogenous intensity function.

Save trained model :param full_path: the path of directory :param mode: 'parameter' for saving only parameters of the mode

Calculate decay kernel's value at time 'dt' :param dt: a 2D Tensor containing the time intervals between current event and historic

Calculate decay kernel's value at time 'dt' :param dt: a 2D Tensor containing the time intervals between current event and historic

Calculate decay kernel's value at time 'dt' :param dt: a 2D Tensor containing the time intervals between current event and historic

Calculate decay kernel's value at time 'dt' :param dt: a 2D Tensor containing the time intervals between current event and historic

Calculate decay kernel's value at time 'dt' :param dt: a 2D Tensor containing the time intervals between current event and historic

Learning optimal transport from source to target domain Args: cost_s: (Ns, Ns) matrix representing the relationships among sourc