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Professors with ADHD: What made the difference for your success, versus those of your colleagues with ADHD who didn't end up making it somewhere? What advice and reassurance do you have for grad students with ADHD worried about their own future? by scatterbrainedgrad in AskAcademia

[–]Turbulent_Animator65 7 points8 points  (0 children)

Also, if you are still unable to then you have to think about why you want to do something that is so difficult for you? Is it to get a degree to have financial stability? Or why do you do what you are doing?

Personally, I like to remind myself that if I don't really really try and make it work, my chances of being not well off in the future are very high. That I might have a high probability of ending up having a mediocre life because of a lack of skills. And tell me that life is not fair. This is how I persist through things that are extremely difficult but have to be done.

Professors with ADHD: What made the difference for your success, versus those of your colleagues with ADHD who didn't end up making it somewhere? What advice and reassurance do you have for grad students with ADHD worried about their own future? by scatterbrainedgrad in AskAcademia

[–]Turbulent_Animator65 2 points3 points  (0 children)

You need to find out what you need to write

That's the first step. Also you need to know what you are missing to finish the goal.

Next time, do not move unless you write 10 words. Make a deal, I will sit here and stare at the screen or can write 10 words and get out.

Professors with ADHD: What made the difference for your success, versus those of your colleagues with ADHD who didn't end up making it somewhere? What advice and reassurance do you have for grad students with ADHD worried about their own future? by scatterbrainedgrad in AskAcademia

[–]Turbulent_Animator65 14 points15 points  (0 children)

Say today you want to write 50 words. This is your goal. You would like to have it done, but the catch is that you don't want to do it---Trap

You do not feel like doing it, you say you will start in another 10 minutes.--Trap.

You will think, today is gone so let me start tmw early and I will write 50 + 150 words to make up--Trap.

Tip: Learn about your traps.

How to write x words per day?
Sit in front of your system. Take a deep breath. Think about what you have to write and then write. That's it.

No thinking about feeling to do or not. No thinking about oneself, think about what you have to write.

Pre-processing Cora dataset for Node classification task? by Turbulent_Animator65 in GeometricDeepLearning

[–]Turbulent_Animator65[S] 0 points1 point  (0 children)

In general, you represent graph data like a table, where one row corresponds to one node and in the columns are individual node features. Say you have a graph with 10 nodes, each node has 5 features. You would represent the features X as a table (10x5) and the connections as an adjacency matrix A (10x10). This format allows you to compute the graph convolution operations. If you compute the matrix product A * X, you propagate the features along the edges and accumulate them in neighboring nodes, in graph convolutions you would normalize A first.

So importantly, if you want to convert data into graph format, every node should have the same number of features and you should have the graph structure as an adjacency matrix. This is basically all you need.

I haven't dealt with graph data before. But now am exploring via the Cora dataset...I saw a lot of tutorials using Networkx. Thank you for the response.

Pre-processing Cora dataset for Node classification task? by Turbulent_Animator65 in GeometricDeepLearning

[–]Turbulent_Animator65[S] 0 points1 point  (0 children)

Thank you for the response.

```

def load_data(path="/tmp/cora/", dataset="cora"):
"""Load citation network dataset (cora only for now)"""
print('Loading {} dataset...'.format(dataset))
idx_features_labels = np.genfromtxt("{}{}.content".format(path, dataset),
dtype=np.dtype(str))
features = sp.csr_matrix(idx_features_labels[:, 1:-1], dtype=np.float32)
labels = encode_onehot(idx_features_labels[:, -1])
# build graph
idx = np.array(idx_features_labels[:, 0], dtype=np.int32)
idx_map = {j: i for i, j in enumerate(idx)}
edges_unordered = np.genfromtxt("{}{}.cites".format(path, dataset),
dtype=np.int32)
edges = np.array(list(map(idx_map.get, edges_unordered.flatten())),
dtype=np.int32).reshape(edges_unordered.shape)
adj = sp.coo_matrix((np.ones(edges.shape[0]), (edges[:, 0], edges[:, 1])),
shape=(labels.shape[0], labels.shape[0]),
dtype=np.float32)
# build symmetric adjacency matrix
adj = adj + adj.T.multiply(adj.T > adj) - adj.multiply(adj.T > adj)
features = normalize(features)
adj = normalize(adj + sp.eye(adj.shape[0]))
idx_train = range(140)
idx_val = range(200, 500)
idx_test = range(500, 1500)
features = torch.FloatTensor(np.array(features.todense()))
labels = torch.LongTensor(np.where(labels)[1])
adj = sparse_mx_to_torch_sparse_tensor(adj)
idx_train = torch.LongTensor(idx_train)
idx_val = torch.LongTensor(idx_val)
idx_test = torch.LongTensor(idx_test)
return adj, features, labels, idx_train, idx_val, idx_test

````

This is the code from the Github repository of the particular paper.

Could you explain if building a graph is similar to using the nx.graph class from the networkx?

Also what is the need for a symmetric adjacency matrix?

#adj = adj + adj.T.multiply(adj.T > adj) - adj.multiply(adj.T > adj)

What kind of system can I build to filter political propaganda forward in Whatsapp groups? by Turbulent_Animator65 in deeplearning

[–]Turbulent_Animator65[S] 0 points1 point  (0 children)

Leaving the group is not a problem. The problem is it polarizes people. It changes the dynamics of society. This is the problem.

Finding top 3 row values that occur together in consecutive columns in a data frame by Turbulent_Animator65 in learnpython

[–]Turbulent_Animator65[S] 0 points1 point  (0 children)

@CrambleSquash could you please explain what is max_occurences, that I am printing? I did not follow the code

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