Ошибка Segmentation fault

Вылетает в этой фукции:

float Neuron::Axon::getSignal() const
{
    return 1 / (1 + exp(ownerNeuron->sum_function()));
}

Функция вызывается из:

float get_axon_value() const {return axon.getSignal(); }

Это функция из

vector<float> Neural_network::test(const vector<float> &in)
{
    set_inputs(in);
    vector<float> out(outNeurons.size());
    for (int i{0}; i < outNeurons.size(); i++)
        out[i] = outNeurons[i].get_axon_value();
    return out;
}

Это точка входа:

Neural_network neuralNetwork;
neuralNetwork.add_input_neuron(Neural_network::Input_neuron());
neuralNetwork.add_out_neuron(Neuron(
        std::vector<Neuron::Dendrite>{Neuron::Dendrite(
                1,
                neuralNetwork.get_input_neuron_ref(0).get_axon_ref()
        )}
));
std::cout << neuralNetwork.test(std::vector<float>{1})[0];

Типы:

/* Axon is the output part of the neuron. Dentrits gets value of neuron from it's Axon.*/
class Axon{
public:
    float getSignal() const;//Activation function
    Neuron *ownerNeuron;
};
/* Dendrite is an input part of neuron. It has weight. It gets value from axon of neron from previous layer.*/
class Dendrite{
public:
    float weight;
    Axon *inputAkson;
    Dendrite(float weight, Axon inAxon) : weight{weight}, inputAkson{&inAxon} {}
};
Neuron::Neuron() : axon()
{
    axon.ownerNeuron = this;
    dendrite.clear();
}
Neuron::Neuron(const vector<Dendrite>& dendrites) : Neuron()
{
    for(Dendrite den : dendrites)
        dendrite.emplace_back(den);
}

class Input_neuron : public Neuron{
    public:
        float sum_function(){
            return value;
        }
        void set_value(float v) { value = v; }
    private:
        float value;
    };

Остальные функции:

void Neural_network::add_input_neuron(const Neural_network::Input_neuron& inputNeuron) {
    inNeurons.emplace_back(inputNeuron);
}
void Neural_network::add_out_neuron(const Neuron& neuron) {
    outNeurons.emplace_back(neuron);
}
Neural_network::Input_neuron &Neural_network::get_input_neuron_ref(int ind) {
    if (ind < 0 || ind >= inNeurons.size())
        throw runtime_error("Neural_network::get_input_neuron_ref(): out of input neurons");
    return inNeurons[ind];
}
Axon& get_axon_ref() { return axon; }